Encoder, decoder, encoding method, and decoding method

ABSTRACT

A decoder includes a memory and processing circuitry. The processing circuitry, in operation, changes values of pixels in a first block and a second block to filter a boundary therebetween, using clipping such that change amounts of the respective values are within respective clip widths. The clip widths for the pixels in the first block and the second block are selected based on block sizes of the first block and the second block. The pixels in the first block include a first pixel located at a first position, and the pixels in the second block include a second pixel located at a second position corresponding to the first position with respect to the boundary. The clip widths include a first clip width and a second clip width corresponding to the first pixel and the second pixel, respectively, and the first clip width is different from the second width.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a continuation application of U.S. application Ser. No.16/450,066, filed Jun. 24, 2019, which is a continuation application ofPCT International Application No. PCT/JP2017/045911 filed on Dec. 21,2017, designating the United States of America, which is based on andclaims priority of U.S. Patent Application No. 62/439,237 filed on Dec.27, 2016. The entire disclosures of the above-identified applications,including the specifications, drawings and claims are incorporatedherein by reference in their entirety.

BACKGROUND 1. Technical Field

The present disclosure relates to an encoder, a decoder, an encodingmethod, and a decoding method.

2. Description of the Related Art

A video coding standard called high-efficiency video coding (HEVC) hasbeen standardized by Joint Collaborative Team on Video Coding (JCT-VC).See H.265 (ISO/IEC 23008-2 HEVC)/HEVC (High Efficiency Video Coding).

SUMMARY

According to one aspect of the present disclosure, an encoder includesprocessing circuitry; and a memory coupled to the processing circuitry.Using the memory, the processing circuitry is configured to: changevalues of pixels in a first block and a second block to filter theboundary between the first block and the second block such that changeamounts of the respective values are smaller than respective thresholds,the pixels being arranged along a line across the boundary; and encode athird block by referring to at least one of the first block or thesecond block after the boundary is filtered. The pixels in the firstblock include a first pixel located at a first position, and the pixelsin the second block include a second pixel located at a second positioncorresponding to the first position with respect to the boundary. Thethresholds include a first threshold and a second thresholdcorresponding to the first pixel and the second pixel, respectively. Thefirst threshold is different from the second threshold.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating a configuration of an encoderaccording to Embodiment 1;

FIG. 2 illustrates one example of block splitting according toEmbodiment 1;

FIG. 3 is a chart indicating transform basis functions for eachtransform type;

FIG. 4A illustrates one example of a filter shape used in ALF;

FIG. 4B illustrates another example of a filter shape used in ALF;

FIG. 4C illustrates another example of a filter shape used in ALF;

FIG. 5A illustrates 67 intra prediction modes used in intra prediction;

FIG. 5B is a flow chart for illustrating an outline of a predictionimage correction process performed via OBMC processing;

FIG. 5C is a conceptual diagram for illustrating an outline of aprediction image correction process performed via OBMC processing;

FIG. 5D illustrates one example of FRUC;

FIG. 6 is for illustrating pattern matching (bilateral matching) betweentwo blocks along a motion trajectory;

FIG. 7 is for illustrating pattern matching (template matching) betweena template in the current picture and a block in a reference picture;

FIG. 8 is for illustrating a model assuming uniform linear motion;

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks;

FIG. 9B is for illustrating an outline of a process for deriving amotion vector via merge mode;

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing;

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing;

FIG. 10 is a block diagram illustrating a configuration of a decoderaccording to Embodiment 1;

FIG. 11 is a flowchart of deblocking filtering according to Embodiment1;

FIG. 12 is a diagram indicating an example of a pixel arrangement at aboundary according to Embodiment 1;

FIG. 13 is a flowchart of deblocking filtering according to Embodiment1;

FIG. 14 is a flowchart of deblocking filtering according to Embodiment2;

FIG. 15 is a diagram indicating relationships between pixel positionsand errors in blocks according to Embodiment 2;

FIG. 16 is a flowchart of deblocking filtering according to Embodiment3;

FIG. 17 is a diagram indicating DCT-II transform basis according toEmbodiment 3;

FIG. 18 is a diagram indicating DST-VII transform basis according toEmbodiment 3;

FIG. 19 is a flowchart of deblocking filtering according to Embodiment4;

FIG. 20 is a flowchart of deblocking filtering according to Embodiment5;

FIG. 21 is a diagram indicating examples of weights based on intraprediction directions and block boundary directions according toEmbodiment 5;

FIG. 22 is a flowchart of deblocking filtering according to Embodiment6;

FIG. 23 is a diagram indicating examples of weights based onquantization parameters according to Embodiment 6;

FIG. 24 is a diagram indicating DCT-II which is an example of a basis;

FIG. 25 is a diagram indicating DST-VII which is an example of a basis;

FIG. 26 is a diagram indicating error distributions of four blocks whichneighbor each other and deblocking-filtered error distributions of thefour blocks;

FIG. 27 is a diagram indicating main constituent elements of a loopfilter according to Embodiment 7;

FIG. 28 is a flowchart indicating schematic processing operationsperformed by the loop filter according to Embodiment 7;

FIG. 29 is a diagram indicating specific constituent elements of theloop filter according to Embodiment 7;

FIG. 30 is a diagram indicating an example of a debloking filter havinga symmetrical filtering characteristic with respect to a block boundary;

FIG. 31 is a diagram indicating an example of DCT-II for each blocksize;

FIG. 32 is a diagram indicating an example of DCT-V for each block size;

FIG. 33 is a diagram indicating an example of DCT-VIII for each blocksize;

FIG. 34 is a diagram indicating an example of DST-I for each block size;

FIG. 35 is a diagram indicating an example of DST-VII for each blocksize;

FIG. 36 is a diagram indicating examples of filter coefficientsdetermined in Embodiment 7;

FIG. 37 is a diagram indicating other examples of filter coefficientsdetermined in Embodiment 7;

FIG. 38 is a diagram indicating still other examples of filtercoefficients determined in Embodiment 7;

FIG. 39 is a diagram for explaining relationships between block sizesand errors;

FIG. 40 is a diagram indicating still other examples of filtercoefficients determined in Embodiment 7;

FIG. 41 is a diagram indicating basis gradients that vary depending onblock sizes;

FIG. 42 is a block diagram indicating a mounting example of an encoderaccording to each of the embodiments;

FIG. 43 is a block diagram indicating a mounting example of a decoderaccording to each of the embodiments;

FIG. 44 illustrates an overall configuration of a content providingsystem for implementing a content distribution service;

FIG. 45 illustrates one example of an encoding structure in scalableencoding;

FIG. 46 illustrates one example of an encoding structure in scalableencoding;

FIG. 47 illustrates an example of a display screen of a web page;

FIG. 48 illustrates an example of a display screen of a web page;

FIG. 49 illustrates one example of a smartphone; and

FIG. 50 is a block diagram illustrating a configuration example of asmartphone.

DETAILED DESCRIPTION OF THE EMBODIMENTS

An encoder according to an aspect of the present disclosure includes:processing circuitry; and memory. Using the memory, for each of blockseach including a plurality of pixels, the processing circuitry:transforms, using a basis, the block into a block including a pluralityof transform coefficients; for each of the blocks each including theplurality of transform coefficients, performs at least inverse transformon the block to reconstruct a block including a plurality of pixels;based on a combination of bases respectively used to transform twoblocks which neighbor each other and have been reconstructed, determinesa filter characteristic for a boundary between the two blocks; andperforms, on the boundary, deblocking filtering with the filtercharacteristic determined.

An error distribution around a boundary between two blocks neighboringeach other varies according to a combination of bases used to transformthe two blocks. For example, transform of the two blocks may cause alarge error in one of the two blocks around the boundary but may cause asmall error around the boundary in the other block. It is to be notedthat each error is the difference between the pixel value of an originalimage or an input image and the pixel value of a reconstructed image.When deblocking filtering with a symmetrical filter characteristic isperformed on the boundary in such a case, the pixel value having thesmall difference may be significantly affected by the pixel value of thepixel having the large error. In other words, there is a possibilitythat errors cannot be sufficiently reduced. In view of this, an encoderaccording an aspect of the present disclosure determines a filtercharacteristic for the boundary between two blocks which neighbor eachother and have been reconstructed, based on a combination of basesrespectively used to transform the two blocks. In this way, for example,an asymmetrical filter characteristic can be determined for theboundary. As a result, even when errors vary around the boundary betweenthe two blocks as described above, it is possible to increase thepossibility of reducing the errors by performing, on the boundary,deblocking filtering with the asymmetrical filter characteristic.

In addition, when determining the filter characteristic, the processingcircuitry may determine, as the filter characteristic, a smaller filtercoefficient for a pixel which is located at a position at which anamplitude of a basis used to transform the block is larger.

For example, a pixel located at a position at which an amplitude of abasis is larger is likely to have a pixel value with a larger error. Theencoder according to an aspect of the present disclosure determines asmall filter coefficient for the pixel having the pixel value with thelarge error. Accordingly, deblocking filtering with such filtercoefficients further reduces influence of the pixel value with the largeerror onto the pixel value with the small error. In short, thedeblocking filtering further increases the possibility of errorreduction.

In addition, the amplitude of the basis may be an amplitude of azero-order basis.

A lower-order basis affects errors more significantly. Accordingly, itis possible to further increase the possibility of error reduction bydetermining a small filter coefficient for a pixel located at a positionat which an amplitude of a zero-order basis is larger.

In addition, the two blocks may be composed of a first block and asecond block located to a right of or below the first block, and whendetermining the filter characteristic. When a basis used to transformthe first block is a first basis, and a basis used to transform thesecond block is a second basis, based on the first basis and the secondbasis, the processing circuitry may determine, as the filtercharacteristic, each of a first filter coefficient for a pixel locatedaround the boundary in the first block and a second filter coefficientfor a pixel located around the boundary in the second block. Forexample, when determining the filter characteristic, the processingcircuitry: when the first basis and the second basis are of DST-VII (DSTdenotes discrete sine transform), may determine, as the filtercoefficient, the second filter coefficient which is larger than thefirst filter coefficient.

In the case where the first basis and the second basis are of DST-VII,it is highly likely that an error in a first block around a boundary islarge and an error in a second block around the boundary is small.Accordingly, it is possible to further increase the possibility ofreducing errors appropriately around the boundary by determining asecond filter coefficient which is larger than a first filtercoefficient in such a case and performing deblocking filtering with thefirst and second filter coefficients.

In addition, when determining the filter characteristic, when the firstbasis and the second basis are of DCT-II (DCT denotes discrete cosinetransform), the processing circuitry may determine, as the filtercoefficient, the second filter coefficient which is equal to the firstfilter coefficient.

In the case where the first basis and the second basis are of DCT-II, itis highly likely that an error in a first block around a boundary and anerror in a second block around the boundary are equal to each other.Accordingly, it is possible to further increase the possibility ofreducing errors appropriately around the boundary by determining asecond filter coefficient which is equal to a first filter coefficientin such a case and performing deblocking filtering with the first andsecond filter coefficients.

In addition, when determining the filter characteristic, when the firstbasis and the second basis are of DST-VII (DST denotes discrete sinetransform), and a size of the second block is smaller than a size of thefirst block, the processing circuitry may determine, as the filtercoefficient, the second filter coefficient which is larger than thefirst filter coefficient. A filter coefficient gradient between thefirst filter coefficient and the second filter coefficient is gentlerthan a filter coefficient gradient in the case where the first block andthe second block are equal in size.

In the case where the first basis and the second basis are of DST-VIIand the size of the second block is smaller than the size of the firstblock, it is likely that an error in the first block around the boundaryis large and an error in the second block around the boundary is at amedium level. In other words, it is likely that an error distributionbetween the first block and the second block around the boundary has agentle gradient.

An encoder according to an aspect of the present disclosure determinesthe second filter coefficient which is larger than the first filtercoefficient in such a case, and performs deblocking filtering with thefirst and second filter coefficients. Here, the determined filtercoefficient gradient between the first filter coefficient and the secondfilter coefficient is gentler than in the case where the first block andthe second block are equal in size. Accordingly, even when the errordistribution around the boundary between the first block and the secondblock has a gentle gradient, it is possible to increase the possibilityof reducing errors appropriately around the boundary.

In addition, when determining the filter characteristic, based on acombination of bases for the first block and the second block, theprocessing circuitry may further determine, as the filtercharacteristic, each of a first threshold value for the first block anda second threshold value for the second block; and when performing thedeblocking filtering, the processing circuitry may: perform acalculation using the first filter coefficient and the second filtercoefficient on a pixel value of a current pixel to obtain a calculatedpixel value of the current pixel; determine whether an amount of changefrom a to-be-calculated pixel value of the current pixel to a calculatedpixel value of the current pixel is larger than one of the firstthreshold value and the second threshold value which is for a block towhich the current pixel belongs among the first block and the secondblock; and when the amount of change is larger than the threshold valuefor the block, clip the calculated pixel value of the current pixel to asum of or a difference between the to-be-calculated pixel value of thecurrent pixel and the threshold value for the block.

In this way, when the amount of change between the to-be-calculatedpixel value of the current pixel and the calculated pixel value islarger than the threshold value, the calculated pixel value of thecurrent pixel is clipped to the sum of or the difference between theto-be-calculated pixel value of the current pixel and the thresholdvalue. Thus, it is possible to prevent the pixel value of the currentpixel from being changed significantly by the deblocking filtering. Inaddition, the first threshold value for the first block and the secondthreshold value for the second block are determined based on thecombination of bases for the first block and the second block.Accordingly, for each of the first block and the second block, it ispossible to determine a large threshold value for a pixel located at aposition at which the amplitude of a basis is large, that is, a pixelhaving a large error, and determine a small threshold value for a pixellocated at a position at which the amplitude of a basis is small, thatis a pixel having a small error. As a result, the deblocking filteringmakes it possible to allow the pixel value of the pixel having the largeerror to change significantly and prohibit the pixel value of the pixelhaving the small error from changing significantly. Accordingly, it isfurther increase the possibility of reducing errors appropriately aroundthe boundary between the first block and the second block.

In addition, using the memory, based on block sizes of a first block anda second block neighboring the first block, the processing circuitrymay: determine a filter characteristic for a boundary between the firstblock and the second block; and perform, on the boundary, deblockingfiltering with the filter characteristic determined. For example, whendetermining the filter characteristic, the processing circuitry may:define, as the filter characteristic, each of a first filter coefficientfor a pixel around the boundary in the first block and a second filtercoefficient for a pixel around the boundary in the second block; anddetermine, as the filter characteristic, the second filter coefficientwhich is larger than the first filter coefficient, when a size of thesecond block is smaller than a size of the first block.

In this way, for example, an asymmetrical filter characteristic can bedetermined for the boundary according to the difference in block size.As a result, even when errors vary around the boundary between twoblocks as described above, it is possible to increase the possibility ofreducing errors by performing deblocking filtering with the asymmetricalfilter characteristic.

A decoder according to an aspect of the present disclosure includes:processing circuitry; and memory. Using the memory, for each of blockseach including a plurality of transform coefficients obtained bytransform using a basis, the processing circuitry: performs at leastinverse transform on the block to reconstruct a block including aplurality of pixels; based on a combination of bases respectively usedto transform two blocks which neighbor each other and have beenreconstructed, determines a filter characteristic for a boundary betweenthe two blocks; and performs, on the boundary, deblocking filtering withthe filter characteristic determined.

An error distribution around a boundary between two blocks neighboringeach other varies according to a combination of bases used to transformthe two blocks. For example, transform of the two blocks may cause alarge error in one of the two blocks around the boundary but may cause asmall error in the other block. It is to be noted that each error is thedifference between the pixel value of an original image or an inputimage and the pixel value of a reconstructed image. When deblockingfiltering with a symmetrical filter characteristic is performed on theboundary in such a case, the pixel value having the small difference maybe significantly affected by the pixel value of the pixel having thelarge error. In other words, there is a possibility that errors cannotbe sufficiently reduced. In view of this, a decoder according an aspectof the present disclosure determines a filter characteristic for theboundary between two blocks which neighbor each other and have beenreconstructed, based on a combination of bases respectively used totransform the two blocks. In this way, for example, an asymmetricalfilter characteristic can be determined for the boundary. As a result,even when errors vary around the boundary between the two blocks asdescribed above, it is possible to increase the possibility of reducingthe errors by performing deblocking filtering with the asymmetricalfilter characteristic.

In addition, when determining the filter characteristic, the processingcircuitry may determine, as the filter characteristic, a smaller filtercoefficient for a pixel which is located at a position at which anamplitude of a basis used to transform the block is larger.

For example, a pixel located at a position at which the amplitude of abasis is larger is likely to have a pixel value with a larger error. Thedecoder according to an aspect of the present disclosure determines asmall filter coefficient for the pixel having the pixel value with thelarge error. Accordingly, deblocking filtering with such filtercoefficients further reduces influence of the pixel value with the largeerror onto the pixel value with the small error. In short, thedeblocking filtering further increases the possibility of errorreduction.

In addition, the amplitude of the basis may be an amplitude of azero-order basis.

A lower-order basis affects errors more significantly. Accordingly, itis possible to further increase the possibility of error reduction bydetermining a small filter coefficient for a pixel located at a positionat which an amplitude of a zero-order basis is larger.

In addition, the two blocks may be composed of a first block and asecond block located to a right of or below the first block, and whendetermining the filter characteristic. When a basis used to transformthe first block is a first basis, and a basis used to transform thesecond block is a second basis, based on the first basis and the secondbasis, the processing circuitry may determine, as the filtercharacteristic, each of a first filter coefficient for a pixel locatedaround the boundary in the first block and a second filter coefficientfor a pixel located around the boundary in the second block. Forexample, in the case where the first basis and the second basis are ofDST-VII (DST denotes discrete sine transforms), when determining thefiltering characteristic, the processing circuitry may determine, as thefilter characteristic, the second filter coefficient which is largerthan the first filter coefficient.

In the case where a first basis and a second basis are of DST-VII, it ishighly likely that an error in a first block around a boundary is largeand an error in a second block around the boundary is small.Accordingly, it is possible to further increase the possibility ofreducing errors appropriately around the boundary by determining asecond filter coefficient which is larger than a first filtercoefficient in such a case and performing deblocking filtering with thefirst and second filter coefficients.

In addition, when determining the filter characteristic, when the firstbasis and the second basis are of DCT-II (DCT denotes discrete cosinetransform), the processing circuitry may determine, as the filtercoefficient, the second filter coefficient which is equal to the firstfilter coefficient.

In the case where the first basis and the second basis are of DCT-II, itis highly likely that an error in a first block around a boundary and anerror in a second block around the boundary are equal to each other.Accordingly, it is possible to further increase the possibility ofreducing errors appropriately around the boundary by determining asecond filter coefficient which is equal to a first filter coefficientin such a case and performing deblocking filtering with the first andsecond filter coefficients.

In addition, when determining the filter characteristic, when the firstbasis and the second basis are of DST-VII (DST denotes discrete sinetransform), and a size of the second block is smaller than a size of thefirst block, the processing circuitry may determine, as the filtercoefficient, the second filter coefficient which is larger than thefirst filter coefficient. A filter coefficient gradient between thefirst filter coefficient and the second filter coefficient is gentlerthan a filter coefficient gradient in the case where the first block andthe second block are equal in size.

In the case where the first basis and the second basis are of DST-VIIand the size of the second block is smaller than the size of the firstblock, it is likely that an error in the first block around the boundaryis large and an error in the second block around the boundary is at amedium level. In other words, it is likely that an error distributionbetween the first block and the second block around the boundary has agentle gradient.

A decoder according to an aspect of the present disclosure determinesthe second filter coefficient larger than the first filter coefficientin such a case, and performs deblocking filtering with the first andsecond filter coefficients. Here, the determined filter coefficientgradient between the first filter coefficient and the second filtercoefficient is gentler than in the case where the first block and thesecond block are equal in size. Accordingly, even when the errordistribution around the boundary between the first block and the secondblock has a gentle gradient, it is possible to increase the possibilityof reducing errors appropriately around the boundary.

In addition, when determining the filter characteristic, based on acombination of bases for the first block and the second block, theprocessing circuitry may further determine, as the filtercharacteristic, each of a first threshold value for the first block anda second threshold value for the second block; and when performing thedeblocking filtering, the processing circuitry: perform a calculationusing the first filter coefficient and the second filter coefficient ona pixel value of a current pixel to obtain a calculated pixel value ofthe current pixel; determine whether an amount of change from ato-be-calculated pixel value of the current pixel to a calculated pixelvalue of the current pixel is larger than one of the first thresholdvalue and the second threshold value which is for a block to which thecurrent pixel belongs among the first block and the second block; andwhen the amount of change is larger than the threshold value for theblock, clip the calculated pixel value of the current pixel to a sum ofor a difference between the to-be-calculated pixel value of the currentpixel and the threshold value for the block. In this way, when theamount of change between the pixel value of a to-be-calculated pixelvalue of a current pixel and the calculated pixel value of the currentpixel is larger than the threshold value, the pixel value of thecalculated current pixel is clipped to the sum of or the differencebetween the to-be-calculated pixel value of the current pixel and thethreshold value. Thus, it is possible to prevent the pixel value of thecurrent pixel from being changed significantly by the deblockingfiltering. In addition, the first threshold value for the first blockand the second threshold value for the second block are determined basedon the combination of bases for the first block and the second block.Accordingly, for each of the first block and the second block, it ispossible to determine a large threshold value for a pixel located at aposition at which the amplitude of a basis is large, that is, a pixelhaving a large error, and determine a small threshold value for a pixellocated at a position at which the amplitude of a basis is small, thatis a pixel having a small error. As a result, the deblocking filteringmakes it possible to allow the pixel value of the pixel having the largeerror to change significantly and prohibit the pixel value of the pixelhaving the small error from changing significantly. Accordingly, it isfurther increase the possibility of reducing errors appropriately aroundthe boundary between the first block and the second block.

In addition, a decoder according to an aspect of the present disclosureincludes: processing circuitry; and memory. Using the memory, based onblock sizes of a first block and a second block neighboring the firstblock, the processing circuitry: determines a filter characteristic fora boundary between the first block and the second block; and performs,on the boundary, deblocking filtering with the filter characteristicdetermined. For example, when determining the filter characteristic, theprocessing circuitry may: define, as the filter characteristic, each ofa first filter coefficient for a pixel around the boundary in the firstblock and a second filter coefficient for a pixel around the boundary inthe second block; and determine, as the filter characteristic, thesecond filter coefficient which is larger than the first filtercoefficient, when a size of the second block is smaller than a size ofthe first block.

In this way, for example, an asymmetrical filter characteristic can bedetermined for the boundary according to the difference in block size.As a result, even when errors vary around the boundary between twoblocks as described above, it is possible to increase the possibility ofreducing errors by performing deblocking filtering with the asymmetricalfilter characteristic.

It is to be noted that these general and specific aspects may beimplemented using a system, a method, an integrated circuit, a computerprogram, or a non-transitory computer-readable recording medium such asa CD-ROM, or any combination of systems, methods, integrated circuits,computer programs, or computer-readable recording media.

Hereinafter, embodiments are described in detail with reference to thedrawings.

It is to be noted that the embodiments described below each show ageneral or specific example. The numerical values, shapes, materials,constituent elements, the arrangement and connection of the constituentelements, steps, order of the steps, etc., indicated in the followingembodiments are mere examples, and therefore are not intended to limitthe scope of the claims. Therefore, among the constituent elements inthe following embodiments, those not recited in any of the independentclaims defining the most generic inventive concepts are described asoptional constituent elements.

Embodiment 1

First, an outline of Embodiment 1 will be presented. Embodiment 1 is oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in subsequent description of aspects of thepresent disclosure are applicable. Note that Embodiment 1 is merely oneexample of an encoder and a decoder to which the processes and/orconfigurations presented in the description of aspects of the presentdisclosure are applicable. The processes and/or configurations presentedin the description of aspects of the present disclosure can also beimplemented in an encoder and a decoder different from those accordingto Embodiment 1.

When the processes and/or configurations presented in the description ofaspects of the present disclosure are applied to Embodiment 1, forexample, any of the following may be performed.

(1) regarding the encoder or the decoder according to Embodiment 1,among components included in the encoder or the decoder according toEmbodiment 1, substituting a component corresponding to a componentpresented in the description of aspects of the present disclosure with acomponent presented in the description of aspects of the presentdisclosure;

(2) regarding the encoder or the decoder according to Embodiment 1,implementing discretionary changes to functions or implemented processesperformed by one or more components included in the encoder or thedecoder according to Embodiment 1, such as addition, substitution, orremoval, etc., of such functions or implemented processes, thensubstituting a component corresponding to a component presented in thedescription of aspects of the present disclosure with a componentpresented in the description of aspects of the present disclosure;

(3) regarding the method implemented by the encoder or the decoderaccording to Embodiment 1, implementing discretionary changes such asaddition of processes and/or substitution, removal of one or more of theprocesses included in the method, and then substituting a processescorresponding to a process presented in the description of aspects ofthe present disclosure with a process presented in the description ofaspects of the present disclosure;

(4) combining one or more components included in the encoder or thedecoder according to Embodiment 1 with a component presented in thedescription of aspects of the present disclosure, a component includingone or more functions included in a component presented in thedescription of aspects of the present disclosure, or a component thatimplements one or more processes implemented by a component presented inthe description of aspects of the present disclosure;

(5) combining a component including one or more functions included inone or more components included in the encoder or the decoder accordingto Embodiment 1, or a component that implements one or more processesimplemented by one or more components included in the encoder or thedecoder according to Embodiment 1 with a component presented in thedescription of aspects of the present disclosure, a component includingone or more functions included in a component presented in thedescription of aspects of the present disclosure, or a component thatimplements one or more processes implemented by a component presented inthe description of aspects of the present disclosure;

(6) regarding the method implemented by the encoder or the decoderaccording to Embodiment 1, among processes included in the method,substituting a process corresponding to a process presented in thedescription of aspects of the present disclosure with a processpresented in the description of aspects of the present disclosure; and

(7) combining one or more processes included in the method implementedby the encoder or the decoder according to Embodiment 1 with a processpresented in the description of aspects of the present disclosure. Notethat the implementation of the processes and/or configurations presentedin the description of aspects of the present disclosure is not limitedto the above examples. For example, the processes and/or configurationspresented in the description of aspects of the present disclosure may beimplemented in a device used for a purpose different from the movingpicture/picture encoder or the moving picture/picture decoder disclosedin Embodiment 1. Moreover, the processes and/or configurations presentedin the description of aspects of the present disclosure may beindependently implemented. Moreover, processes and/or configurationsdescribed in different aspects may be combined.

[Encoder Outline]

First, the encoder according to Embodiment 1 will be outlined. FIG. 1 isa block diagram illustrating a configuration of encoder 100 according toEmbodiment 1. Encoder 100 is a moving picture/picture encoder thatencodes a moving picture/picture block by block.

As illustrated in FIG. 1 , encoder 100 is a device that encodes apicture block by block, and includes splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, block memory 118, loop filter120, frame memory 122, intra predictor 124, inter predictor 126, andprediction controller 128.

Encoder 100 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as splitter 102, subtractor104, transformer 106, quantizer 108, entropy encoder 110, inversequantizer 112, inverse transformer 114, adder 116, loop filter 120,intra predictor 124, inter predictor 126, and prediction controller 128.Alternatively, encoder 100 may be realized as one or more dedicatedelectronic circuits corresponding to splitter 102, subtractor 104,transformer 106, quantizer 108, entropy encoder 110, inverse quantizer112, inverse transformer 114, adder 116, loop filter 120, intrapredictor 124, inter predictor 126, and prediction controller 128.

Hereinafter, each component included in encoder 100 will be described.

[Splitter]

Splitter 102 splits each picture included in an input moving pictureinto blocks, and outputs each block to subtractor 104. For example,splitter 102 first splits a picture into blocks of a fixed size (forexample, 128×128). The fixed size block is also referred to as codingtree unit (CTU). Splitter 102 then splits each fixed size block intoblocks of variable sizes (for example, 64×64 or smaller), based onrecursive quadtree and/or binary tree block splitting. The variable sizeblock is also referred to as a coding unit (CU), a prediction unit (PU),or a transform unit (TU). Note that in this embodiment, there is no needto differentiate between CU, PU, and TU; all or some of the blocks in apicture may be processed per CU, PU, or TU.

FIG. 2 illustrates one example of block splitting according toEmbodiment 1. In FIG. 2 , the solid lines represent block boundaries ofblocks split by quadtree block splitting, and the dashed lines representblock boundaries of blocks split by binary tree block splitting.

Here, block 10 is a square 128×128 pixel block (128×128 block). This128×128 block 10 is first split into four square 64×64 blocks (quadtreeblock splitting).

The top left 64×64 block is further vertically split into two rectangle32×64 blocks, and the left 32×64 block is further vertically split intotwo rectangle 16×64 blocks (binary tree block splitting). As a result,the top left 64×64 block is split into two 16×64 blocks 11 and 12 andone 32×64 block 13.

The top right 64×64 block is horizontally split into two rectangle 64×32blocks 14 and 15 (binary tree block splitting).

The bottom left 64×64 block is first split into four square 32×32 blocks(quadtree block splitting). The top left block and the bottom rightblock among the four 32×32 blocks are further split. The top left 32×32block is vertically split into two rectangle 16×32 blocks, and the right16×32 block is further horizontally split into two 16×16 blocks (binarytree block splitting). The bottom right 32×32 block is horizontallysplit into two 32×16 blocks (binary tree block splitting). As a result,the bottom left 64×64 block is split into 16×32 block 16, two 16×16blocks 17 and 18, two 32×32 blocks 19 and 20, and two 32×16 blocks 21and 22.

The bottom right 64×64 block 23 is not split.

As described above, in FIG. 2 , block 10 is split into 13 variable sizeblocks 11 through 23 based on recursive quadtree and binary tree blocksplitting. This type of splitting is also referred to as quadtree plusbinary tree (QTBT) splitting.

Note that in FIG. 2 , one block is split into four or two blocks(quadtree or binary tree block splitting), but splitting is not limitedto this example. For example, one block may be split into three blocks(ternary block splitting). Splitting including such ternary blocksplitting is also referred to as multi-type tree (MBT) splitting.

[Subtractor]

Subtractor 104 subtracts a prediction signal (prediction sample) from anoriginal signal (original sample) per block split by splitter 102. Inother words, subtractor 104 calculates prediction errors (also referredto as residuals) of a block to be encoded (hereinafter referred to as acurrent block). Subtractor 104 then outputs the calculated predictionerrors to transformer 106.

The original signal is a signal input into encoder 100, and is a signalrepresenting an image for each picture included in a moving picture (forexample, a luma signal and two chroma signals). Hereinafter, a signalrepresenting an image is also referred to as a sample.

[Transformer]

Transformer 106 transforms spatial domain prediction errors intofrequency domain transform coefficients, and outputs the transformcoefficients to quantizer 108. More specifically, transformer 106applies, for example, a predefined discrete cosine transform (DCT) ordiscrete sine transform (DST) to spatial domain prediction errors.

Note that transformer 106 may adaptively select a transform type fromamong a plurality of transform types, and transform prediction errorsinto transform coefficients by using a transform basis functioncorresponding to the selected transform type. This sort of transform isalso referred to as explicit multiple core transform (EMT) or adaptivemultiple transform (AMT).

The transform types include, for example, DCT-II, DCT-V, DCT-VIII,DST-I, and DST-VII. FIG. 3 is a chart indicating transform basisfunctions for each transform type. In FIG. 3 , N indicates the number ofinput pixels. For example, selection of a transform type from among theplurality of transform types may depend on the prediction type (intraprediction and inter prediction), and may depend on intra predictionmode.

Information indicating whether to apply such EMT or AMT (referred to as,for example, an AMT flag) and information indicating the selectedtransform type is signalled at the CU level. Note that the signaling ofsuch information need not be performed at the CU level, and may beperformed at another level (for example, at the sequence level, picturelevel, slice level, tile level, or CTU level).

Moreover, transformer 106 may apply a secondary transform to thetransform coefficients (transform result). Such a secondary transform isalso referred to as adaptive secondary transform (AST) or non-separablesecondary transform (NSST). For example, transformer 106 applies asecondary transform to each sub-block (for example, each 4×4 sub-block)included in the block of the transform coefficients corresponding to theintra prediction errors. Information indicating whether to apply NSSTand information related to the transform matrix used in NSST aresignalled at the CU level. Note that the signaling of such informationneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, or CTU level).

Here, a separable transform is a method in which a transform isperformed a plurality of times by separately performing a transform foreach direction according to the number of dimensions input. Anon-separable transform is a method of performing a collective transformin which two or more dimensions in a multidimensional input arecollectively regarded as a single dimension.

In one example of a non-separable transform, when the input is a 4×4block, the 4×4 block is regarded as a single array including 16components, and the transform applies a 16×16 transform matrix to thearray.

Moreover, similar to above, after an input 4×4 block is regarded as asingle array including 16 components, a transform that performs aplurality of Givens rotations on the array (i.e., a Hypercube-GivensTransform) is also one example of a non-separable transform.

[Quantizer]

Quantizer 108 quantizes the transform coefficients output fromtransformer 106. More specifically, quantizer 108 scans, in apredetermined scanning order, the transform coefficients of the currentblock, and quantizes the scanned transform coefficients based onquantization parameters (QP) corresponding to the transformcoefficients. Quantizer 108 then outputs the quantized transformcoefficients (hereinafter referred to as quantized coefficients) of thecurrent block to entropy encoder 110 and inverse quantizer 112.

A predetermined order is an order for quantizing/inverse quantizingtransform coefficients. For example, a predetermined scanning order isdefined as ascending order of frequency (from low to high frequency) ordescending order of frequency (from high to low frequency).

A quantization parameter is a parameter defining a quantization stepsize (quantization width). For example, if the value of the quantizationparameter increases, the quantization step size also increases. In otherwords, if the value of the quantization parameter increases, thequantization error increases.

[Entropy Encoder]

Entropy encoder 110 generates an encoded signal (encoded bitstream) byvariable length encoding quantized coefficients, which are inputs fromquantizer 108. More specifically, entropy encoder 110, for example,binarizes quantized coefficients and arithmetic encodes the binarysignal.

[Inverse Quantizer]

Inverse quantizer 112 inverse quantizes quantized coefficients, whichare inputs from quantizer 108. More specifically, inverse quantizer 112inverse quantizes, in a predetermined scanning order, quantizedcoefficients of the current block. Inverse quantizer 112 then outputsthe inverse quantized transform coefficients of the current block toinverse transformer 114.

[Inverse Transformer]

Inverse transformer 114 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 112. More specifically, inverse transformer 114 restores theprediction errors of the current block by applying an inverse transformcorresponding to the transform applied by transformer 106 on thetransform coefficients. Inverse transformer 114 then outputs therestored prediction errors to adder 116.

Note that since information is lost in quantization, the restoredprediction errors do not match the prediction errors calculated bysubtractor 104. In other words, the restored prediction errors includequantization errors.

[Adder]

Adder 116 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 114, and prediction samples,which are inputs from prediction controller 128. Adder 116 then outputsthe reconstructed block to block memory 118 and loop filter 120. Areconstructed block is also referred to as a local decoded block.

[Block Memory]

Block memory 118 is storage for storing blocks in a picture to beencoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 118 storesreconstructed blocks output from adder 116.

[Loop Filter]

Loop filter 120 applies a loop filter to blocks reconstructed by adder116, and outputs the filtered reconstructed blocks to frame memory 122.A loop filter is a filter used in an encoding loop (in-loop filter), andincludes, for example, a deblocking filter (DF), a sample adaptiveoffset (SAO), and an adaptive loop filter (ALF).

In ALF, a least square error filter for removing compression artifactsis applied. For example, one filter from among a plurality of filters isselected for each 2×2 sub-block in the current block based on directionand activity of local gradients, and is applied.

More specifically, first, each sub-block (for example, each 2×2sub-block) is categorized into one out of a plurality of classes (forexample, 15 or 25 classes). The classification of the sub-block is basedon gradient directionality and activity. For example, classificationindex C is derived based on gradient directionality D (for example, 0 to2 or 0 to 4) and gradient activity A (for example, 0 to 4) (for example,C=5D+A). Then, based on classification index C, each sub-block iscategorized into one out of a plurality of classes (for example, 15 or25 classes).

For example, gradient directionality D is calculated by comparinggradients of a plurality of directions (for example, the horizontal,vertical, and two diagonal directions). Moreover, for example, gradientactivity A is calculated by summing gradients of a plurality ofdirections and quantizing the sum.

The filter to be used for each sub-block is determined from among theplurality of filters based on the result of such categorization.

The filter shape to be used in ALF is, for example, a circular symmetricfilter shape. FIG. 4A through FIG. 4C illustrate examples of filtershapes used in ALF. FIG. 4A illustrates a 5×5 diamond shape filter, FIG.4B illustrates a 7×7 diamond shape filter, and FIG. 4C illustrates a 9×9diamond shape filter. Information indicating the filter shape issignalled at the picture level. Note that the signaling of informationindicating the filter shape need not be performed at the picture level,and may be performed at another level (for example, at the sequencelevel, slice level, tile level, CTU level, or CU level).

The enabling or disabling of ALF is determined at the picture level orCU level. For example, for luma, the decision to apply ALF or not isdone at the CU level, and for chroma, the decision to apply ALF or notis done at the picture level. Information indicating whether ALF isenabled or disabled is signalled at the picture level or CU level. Notethat the signaling of information indicating whether ALF is enabled ordisabled need not be performed at the picture level or CU level, and maybe performed at another level (for example, at the sequence level, slicelevel, tile level, or CTU level).

The coefficients set for the plurality of selectable filters (forexample, 15 or 25 filters) is signalled at the picture level. Note thatthe signaling of the coefficients set need not be performed at thepicture level, and may be performed at another level (for example, atthe sequence level, slice level, tile level, CTU level, CU level, orsub-block level).

[Frame Memory]

Frame memory 122 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 122 stores reconstructed blocks filtered byloop filter 120.

[Intra Predictor]

Intra predictor 124 generates a prediction signal (intra predictionsignal) by intra predicting the current block with reference to a blockor blocks in the current picture and stored in block memory 118 (alsoreferred to as intra frame prediction). More specifically, intrapredictor 124 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 128.

For example, intra predictor 124 performs intra prediction by using onemode from among a plurality of predefined intra prediction modes. Theintra prediction modes include one or more non-directional predictionmodes and a plurality of directional prediction modes.

The one or more non-directional prediction modes include, for example,planar prediction mode and DC prediction mode defined in theH.265/high-efficiency video coding (HEVC) standard (see NPTL 1).

The plurality of directional prediction modes include, for example, the33 directional prediction modes defined in the H.265/HEVC standard. Notethat the plurality of directional prediction modes may further include32 directional prediction modes in addition to the 33 directionalprediction modes (for a total of 65 directional prediction modes). FIG.5A illustrates 67 intra prediction modes used in intra prediction (twonon-directional prediction modes and 65 directional prediction modes).The solid arrows represent the 33 directions defined in the H.265/HEVCstandard, and the dashed arrows represent the additional 32 directions.

Note that a luma block may be referenced in chroma block intraprediction. In other words, a chroma component of the current block maybe predicted based on a luma component of the current block. Such intraprediction is also referred to as cross-component linear model (CCLM)prediction. Such a chroma block intra prediction mode that references aluma block (referred to as, for example, CCLM mode) may be added as oneof the chroma block intra prediction modes.

Intra predictor 124 may correct post-intra-prediction pixel values basedon horizontal/vertical reference pixel gradients. Intra predictionaccompanied by this sort of correcting is also referred to as positiondependent intra prediction combination (PDPC). Information indicatingwhether to apply PDPC or not (referred to as, for example, a PDPC flag)is, for example, signalled at the CU level. Note that the signaling ofthis information need not be performed at the CU level, and may beperformed at another level (for example, on the sequence level, picturelevel, slice level, tile level, or CTU level).

[Inter Predictor]

Inter predictor 126 generates a prediction signal (inter predictionsignal) by inter predicting the current block with reference to a blockor blocks in a reference picture, which is different from the currentpicture and is stored in frame memory 122 (also referred to as interframe prediction). Inter prediction is performed per current block orper sub-block (for example, per 4×4 block) in the current block. Forexample, inter predictor 126 performs motion estimation in a referencepicture for the current block or sub-block. Inter predictor 126 thengenerates an inter prediction signal of the current block or sub-blockby motion compensation by using motion information (for example, amotion vector) obtained from motion estimation. Inter predictor 126 thenoutputs the generated inter prediction signal to prediction controller128.

The motion information used in motion compensation is signalled. Amotion vector predictor may be used for the signaling of the motionvector. In other words, the difference between the motion vector and themotion vector predictor may be signalled.

Note that the inter prediction signal may be generated using motioninformation for a neighboring block in addition to motion informationfor the current block obtained from motion estimation. Morespecifically, the inter prediction signal may be generated per sub-blockin the current block by calculating a weighted sum of a predictionsignal based on motion information obtained from motion estimation and aprediction signal based on motion information for a neighboring block.Such inter prediction (motion compensation) is also referred to asoverlapped block motion compensation (OBMC).

In such an OBMC mode, information indicating sub-block size for OBMC(referred to as, for example, OBMC block size) is signalled at thesequence level. Moreover, information indicating whether to apply theOBMC mode or not (referred to as, for example, an OBMC flag) issignalled at the CU level. Note that the signaling of such informationneed not be performed at the sequence level and CU level, and may beperformed at another level (for example, at the picture level, slicelevel, tile level, CTU level, or sub-block level).

Hereinafter, the OBMC mode will be described in further detail. FIG. 5Bis a flowchart and FIG. 5C is a conceptual diagram for illustrating anoutline of a prediction image correction process performed via OBMCprocessing.

First, a prediction image (Pred) is obtained through typical motioncompensation using a motion vector (MV) assigned to the current block.

Next, a prediction image (Pred_L) is obtained by applying a motionvector (MV L) of the encoded neighboring left block to the currentblock, and a first pass of the correction of the prediction image ismade by superimposing the prediction image and Pred_L.

Similarly, a prediction image (Pred_U) is obtained by applying a motionvector (MV_U) of the encoded neighboring upper block to the currentblock, and a second pass of the correction of the prediction image ismade by superimposing the prediction image resulting from the first passand Pred_U. The result of the second pass is the final prediction image.

Note that the above example is of a two-pass correction method using theneighboring left and upper blocks, but the method may be a three-pass orhigher correction method that also uses the neighboring right and/orlower block.

Note that the region subject to superimposition may be the entire pixelregion of the block, and, alternatively, may be a partial block boundaryregion.

Note that here, the prediction image correction process is described asbeing based on a single reference picture, but the same applies when aprediction image is corrected based on a plurality of referencepictures. In such a case, after corrected prediction images resultingfrom performing correction based on each of the reference pictures areobtained, the obtained corrected prediction images are furthersuperimposed to obtain the final prediction image.

Note that the unit of the current block may be a prediction block and,alternatively, may be a sub-block obtained by further dividing theprediction block.

One example of a method for determining whether to implement OBMCprocessing is by using an obmc_flag, which is a signal that indicateswhether to implement OBMC processing. As one specific example, theencoder determines whether the current block belongs to a regionincluding complicated motion. The encoder sets the obmc_flag to a valueof “1” when the block belongs to a region including complicated motionand implements OBMC processing when encoding, and sets the obmc_flag toa value of “0” when the block does not belong to a region includingcomplication motion and encodes without implementing OBMC processing.The decoder switches between implementing OBMC processing or not bydecoding the obmc_flag written in the stream and performing the decodingin accordance with the flag value.

Note that the motion information may be derived on the decoder sidewithout being signalled. For example, a merge mode defined in theH.265/HEVC standard may be used. Moreover, for example, the motioninformation may be derived by performing motion estimation on thedecoder side. In this case, motion estimation is performed without usingthe pixel values of the current block.

Here, a mode for performing motion estimation on the decoder side willbe described. A mode for performing motion estimation on the decoderside is also referred to as pattern matched motion vector derivation(PMMVD) mode or frame rate up-conversion (FRUC) mode.

One example of FRUC processing is illustrated in FIG. 5D. First, acandidate list (a candidate list may be a merge list) of candidates eachincluding a motion vector predictor is generated with reference tomotion vectors of encoded blocks that spatially or temporally neighborthe current block. Next, the best candidate MV is selected from among aplurality of candidate MVs registered in the candidate list. Forexample, evaluation values for the candidates included in the candidatelist are calculated and one candidate is selected based on thecalculated evaluation values.

Next, a motion vector for the current block is derived from the motionvector of the selected candidate. More specifically, for example, themotion vector for the current block is calculated as the motion vectorof the selected candidate (best candidate MV), as-is. Alternatively, themotion vector for the current block may be derived by pattern matchingperformed in the vicinity of a position in a reference picturecorresponding to the motion vector of the selected candidate. In otherwords, when the vicinity of the best candidate MV is searched via thesame method and an MV having a better evaluation value is found, thebest candidate MV may be updated to the MV having the better evaluationvalue, and the MV having the better evaluation value may be used as thefinal MV for the current block. Note that a configuration in which thisprocessing is not implemented is also acceptable.

The same processes may be performed in cases in which the processing isperformed in units of sub-blocks.

Note that an evaluation value is calculated by calculating thedifference in the reconstructed image by pattern matching performedbetween a region in a reference picture corresponding to a motion vectorand a predetermined region. Note that the evaluation value may becalculated by using some other information in addition to thedifference.

The pattern matching used is either first pattern matching or secondpattern matching. First pattern matching and second pattern matching arealso referred to as bilateral matching and template matching,respectively.

In the first pattern matching, pattern matching is performed between twoblocks along the motion trajectory of the current block in two differentreference pictures. Therefore, in the first pattern matching, a regionin another reference picture conforming to the motion trajectory of thecurrent block is used as the predetermined region for theabove-described calculation of the candidate evaluation value.

FIG. 6 is for illustrating one example of pattern matching (bilateralmatching) between two blocks along a motion trajectory. As illustratedin FIG. 6 , in the first pattern matching, two motion vectors (MV0, MV1)are derived by finding the best match between two blocks along themotion trajectory of the current block (Cur block) in two differentreference pictures (Ref0, Ref1). More specifically, a difference between(i) a reconstructed image in a specified position in a first encodedreference picture (Ref0) specified by a candidate MV and (ii) areconstructed picture in a specified position in a second encodedreference picture (Ref1) specified by a symmetrical MV scaled at adisplay time interval of the candidate MV may be derived, and theevaluation value for the current block may be calculated by using thederived difference. The candidate MV having the best evaluation valueamong the plurality of candidate MVs may be selected as the final MV.

Under the assumption of continuous motion trajectory, the motion vectors(MV0, MV1) pointing to the two reference blocks shall be proportional tothe temporal distances (TD0, TD1) between the current picture (Cur Pic)and the two reference pictures (Ref0, Ref1). For example, when thecurrent picture is temporally between the two reference pictures and thetemporal distance from the current picture to the two reference picturesis the same, the first pattern matching derives a mirror basedbi-directional motion vector.

In the second pattern matching, pattern matching is performed between atemplate in the current picture (blocks neighboring the current block inthe current picture (for example, the top and/or left neighboringblocks)) and a block in a reference picture. Therefore, in the secondpattern matching, a block neighboring the current block in the currentpicture is used as the predetermined region for the above-describedcalculation of the candidate evaluation value.

FIG. 7 is for illustrating one example of pattern matching (templatematching) between a template in the current picture and a block in areference picture. As illustrated in FIG. 7 , in the second patternmatching, a motion vector of the current block is derived by searching areference picture (Ref0) to find the block that best matches neighboringblocks of the current block (Cur block) in the current picture (CurPic). More specifically, a difference between (i) a reconstructed imageof an encoded region that is both or one of the neighboring left andneighboring upper region and (ii) a reconstructed picture in the sameposition in an encoded reference picture (Ref0) specified by a candidateMV may be derived, and the evaluation value for the current block may becalculated by using the derived difference. The candidate MV having thebest evaluation value among the plurality of candidate MVs may beselected as the best candidate MV.

Information indicating whether to apply the FRUC mode or not (referredto as, for example, a FRUC flag) is signalled at the CU level. Moreover,when the FRUC mode is applied (for example, when the FRUC flag is set totrue), information indicating the pattern matching method (first patternmatching or second pattern matching) is signalled at the CU level. Notethat the signaling of such information need not be performed at the CUlevel, and may be performed at another level (for example, at thesequence level, picture level, slice level, tile level, CTU level, orsub-block level).

Here, a mode for deriving a motion vector based on a model assuminguniform linear motion will be described. This mode is also referred toas a bi-directional optical flow (BIO) mode.

FIG. 8 is for illustrating a model assuming uniform linear motion. InFIG. 8 , (v_(x), v_(y)) denotes a velocity vector, and to and τ₁ denotetemporal distances between the current picture (Cur Pic) and tworeference pictures (Ref₀, Ref₁). (MVx₀, MVy₀) denotes a motion vectorcorresponding to reference picture Ref₀, and (MVx₁, MVy₁) denotes amotion vector corresponding to reference picture Ref₁.

Here, under the assumption of uniform linear motion exhibited byvelocity vector (v_(x), v_(y)), (MVx₀, MVy₀) and (MVx₁, MVy₁) arerepresented as (v_(x)τ₀, v_(y)τ₀) and (−v_(x)τ₁, −v_(y)τ₁),respectively, and the following optical flow equation is given.MATH. 1∂I ^((k)) /∂t+v _(x) ∂I ^((k)) /∂x+v _(y) ∂I ^((k)) /∂y=0.  (1)

Here, I^((k)) denotes a luma value from reference picture k (k=0, 1)after motion compensation. This optical flow equation shows that the sumof (i) the time derivative of the luma value, (ii) the product of thehorizontal velocity and the horizontal component of the spatial gradientof a reference picture, and (iii) the product of the vertical velocityand the vertical component of the spatial gradient of a referencepicture is equal to zero. A motion vector of each block obtained from,for example, a merge list is corrected pixel by pixel based on acombination of the optical flow equation and Hermite interpolation.

Note that a motion vector may be derived on the decoder side using amethod other than deriving a motion vector based on a model assuminguniform linear motion. For example, a motion vector may be derived foreach sub-block based on motion vectors of neighboring blocks.

Here, a mode in which a motion vector is derived for each sub-blockbased on motion vectors of neighboring blocks will be described. Thismode is also referred to as affine motion compensation prediction mode.

FIG. 9A is for illustrating deriving a motion vector of each sub-blockbased on motion vectors of neighboring blocks. In FIG. 9A, the currentblock includes 16 4×4 sub-blocks. Here, motion vector v₀ of the top leftcorner control point in the current block is derived based on motionvectors of neighboring sub-blocks, and motion vector v₁ of the top rightcorner control point in the current block is derived based on motionvectors of neighboring blocks. Then, using the two motion vectors v₀ andv₁, the motion vector (v_(x), v_(y)) of each sub-block in the currentblock is derived using Equation 2 below.

$\begin{matrix}{{MATH}.\mspace{14mu} 2} & \; \\\left\{ \begin{matrix}{v_{ϰ} = {{\frac{\left( {v_{1ϰ} - v_{0ϰ}} \right)}{w}ϰ} - {\frac{\left( {v_{1y} - v_{0y}} \right)}{w}y} + v_{0ϰ}}} \\{v_{y} = {{\frac{\left( {v_{1y} - v_{0y}} \right)}{w}ϰ} + {\frac{\left( {v_{1ϰ} - v_{0ϰ}} \right)}{w}y} + v_{0y}}}\end{matrix} \right. & (2)\end{matrix}$

Here, x and y are the horizontal and vertical positions of thesub-block, respectively, and w is a predetermined weighted coefficient.

Such an affine motion compensation prediction mode may include a numberof modes of different methods of deriving the motion vectors of the topleft and top right corner control points. Information indicating such anaffine motion compensation prediction mode (referred to as, for example,an affine flag) is signalled at the CU level. Note that the signaling ofinformation indicating the affine motion compensation prediction modeneed not be performed at the CU level, and may be performed at anotherlevel (for example, at the sequence level, picture level, slice level,tile level, CTU level, or sub-block level).

[Prediction Controller]

Prediction controller 128 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto subtractor 104 and adder 116.

Here, an example of deriving a motion vector via merge mode in a currentpicture will be given. FIG. 9B is for illustrating an outline of aprocess for deriving a motion vector via merge mode.

First, an MV predictor list in which candidate MV predictors areregistered is generated. Examples of candidate MV predictors include:spatially neighboring MV predictors, which are MVs of encoded blockspositioned in the spatial vicinity of the current block; a temporallyneighboring MV predictor, which is an MV of a block in an encodedreference picture that neighbors a block in the same location as thecurrent block; a combined MV predictor, which is an MV generated bycombining the MV values of the spatially neighboring MV predictor andthe temporally neighboring MV predictor; and a zero MV predictor, whichis an MV whose value is zero.

Next, the MV of the current block is determined by selecting one MVpredictor from among the plurality of MV predictors registered in the MVpredictor list.

Furthermore, in the variable-length encoder, a merge_idx, which is asignal indicating which MV predictor is selected, is written and encodedinto the stream.

Note that the MV predictors registered in the MV predictor listillustrated in FIG. 9B constitute one example. The number of MVpredictors registered in the MV predictor list may be different from thenumber illustrated in FIG. 9B, the MV predictors registered in the MVpredictor list may omit one or more of the types of MV predictors givenin the example in FIG. 9B, and the MV predictors registered in the MVpredictor list may include one or more types of MV predictors inaddition to and different from the types given in the example in FIG.9B.

Note that the final MV may be determined by performing DMVR processing(to be described later) by using the MV of the current block derived viamerge mode.

Here, an example of determining an MV by using DMVR processing will begiven.

FIG. 9C is a conceptual diagram for illustrating an outline of DMVRprocessing.

First, the most appropriate MVP set for the current block is consideredto be the candidate MV, reference pixels are obtained from a firstreference picture, which is a picture processed in the L0 direction inaccordance with the candidate MV, and a second reference picture, whichis a picture processed in the L1 direction in accordance with thecandidate MV, and a template is generated by calculating the average ofthe reference pixels.

Next, using the template, the surrounding regions of the candidate MVsof the first and second reference pictures are searched, and the MV withthe lowest cost is determined to be the final MV. Note that the costvalue is calculated using, for example, the difference between eachpixel value in the template and each pixel value in the regionssearched, as well as the MV value.

Note that the outlines of the processes described here are fundamentallythe same in both the encoder and the decoder.

Note that processing other than the processing exactly as describedabove may be used, so long as the processing is capable of deriving thefinal MV by searching the surroundings of the candidate MV.

Here, an example of a mode that generates a prediction image by usingLIC processing will be given.

FIG. 9D is for illustrating an outline of a prediction image generationmethod using a luminance correction process performed via LICprocessing.

First, an MV is extracted for obtaining, from an encoded referencepicture, a reference image corresponding to the current block.

Next, information indicating how the luminance value changed between thereference picture and the current picture is extracted and a luminancecorrection parameter is calculated by using the luminance pixel valuesfor the encoded left neighboring reference region and the encoded upperneighboring reference region, and the luminance pixel value in the samelocation in the reference picture specified by the MV.

The prediction image for the current block is generated by performing aluminance correction process by using the luminance correction parameteron the reference image in the reference picture specified by the MV.

Note that the shape of the surrounding reference region illustrated inFIG. 9D is just one example; the surrounding reference region may have adifferent shape.

Moreover, although a prediction image is generated from a singlereference picture in this example, in cases in which a prediction imageis generated from a plurality of reference pictures as well, theprediction image is generated after performing a luminance correctionprocess, via the same method, on the reference images obtained from thereference pictures.

One example of a method for determining whether to implement LICprocessing is by using an lic_flag, which is a signal that indicateswhether to implement LIC processing. As one specific example, theencoder determines whether the current block belongs to a region ofluminance change. The encoder sets the lic_flag to a value of “1” whenthe block belongs to a region of luminance change and implements LICprocessing when encoding, and sets the lic_flag to a value of “0” whenthe block does not belong to a region of luminance change and encodeswithout implementing LIC processing. The decoder switches betweenimplementing LIC processing or not by decoding the lic_flag written inthe stream and performing the decoding in accordance with the flagvalue.

One example of a different method of determining whether to implementLIC processing is determining so in accordance with whether LICprocessing was determined to be implemented for a surrounding block. Inone specific example, when merge mode is used on the current block,whether LIC processing was applied in the encoding of the surroundingencoded block selected upon deriving the MV in the merge mode processingmay be determined, and whether to implement LIC processing or not can beswitched based on the result of the determination. Note that in thisexample, the same applies to the processing performed on the decoderside.

[Decoder Outline]

Next, a decoder capable of decoding an encoded signal (encodedbitstream) output from encoder 100 will be described. FIG. 10 is a blockdiagram illustrating a configuration of decoder 200 according toEmbodiment 1. Decoder 200 is a moving picture/picture decoder thatdecodes a moving picture/picture block by block.

As illustrated in FIG. 10 , decoder 200 includes entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, block memory210, loop filter 212, frame memory 214, intra predictor 216, interpredictor 218, and prediction controller 220.

Decoder 200 is realized as, for example, a generic processor and memory.In this case, when a software program stored in the memory is executedby the processor, the processor functions as entropy decoder 202,inverse quantizer 204, inverse transformer 206, adder 208, loop filter212, intra predictor 216, inter predictor 218, and prediction controller220. Alternatively, decoder 200 may be realized as one or more dedicatedelectronic circuits corresponding to entropy decoder 202, inversequantizer 204, inverse transformer 206, adder 208, loop filter 212,intra predictor 216, inter predictor 218, and prediction controller 220.

Hereinafter, each component included in decoder 200 will be described.

[Entropy Decoder]

Entropy decoder 202 entropy decodes an encoded bitstream. Morespecifically, for example, entropy decoder 202 arithmetic decodes anencoded bitstream into a binary signal. Entropy decoder 202 thendebinarizes the binary signal. With this, entropy decoder 202 outputsquantized coefficients of each block to inverse quantizer 204.

[Inverse Quantizer]

Inverse quantizer 204 inverse quantizes quantized coefficients of ablock to be decoded (hereinafter referred to as a current block), whichare inputs from entropy decoder 202. More specifically, inversequantizer 204 inverse quantizes quantized coefficients of the currentblock based on quantization parameters corresponding to the quantizedcoefficients. Inverse quantizer 204 then outputs the inverse quantizedcoefficients (i.e., transform coefficients) of the current block toinverse transformer 206.

[Inverse Transformer]

Inverse transformer 206 restores prediction errors by inversetransforming transform coefficients, which are inputs from inversequantizer 204.

For example, when information parsed from an encoded bitstream indicatesapplication of EMT or AMT (for example, when the AMT flag is set totrue), inverse transformer 206 inverse transforms the transformcoefficients of the current block based on information indicating theparsed transform type. Moreover, for example, when information parsedfrom an encoded bitstream indicates application of NSST, inversetransformer 206 applies a secondary inverse transform to the transformcoefficients.

[Adder]

Adder 208 reconstructs the current block by summing prediction errors,which are inputs from inverse transformer 206, and prediction samples,which is an input from prediction controller 220. Adder 208 then outputsthe reconstructed block to block memory 210 and loop filter 212.

[Block Memory]

Block memory 210 is storage for storing blocks in a picture to bedecoded (hereinafter referred to as a current picture) for reference inintra prediction. More specifically, block memory 210 storesreconstructed blocks output from adder 208.

[Loop Filter]

Loop filter 212 applies a loop filter to blocks reconstructed by adder208, and outputs the filtered reconstructed blocks to frame memory 214and, for example, a display device.

When information indicating the enabling or disabling of ALF parsed froman encoded bitstream indicates enabled, one filter from among aplurality of filters is selected based on direction and activity oflocal gradients, and the selected filter is applied to the reconstructedblock.

[Frame Memory]

Frame memory 214 is storage for storing reference pictures used in interprediction, and is also referred to as a frame buffer. Morespecifically, frame memory 214 stores reconstructed blocks filtered byloop filter 212.

[Intra Predictor]

Intra predictor 216 generates a prediction signal (intra predictionsignal) by intra prediction with reference to a block or blocks in thecurrent picture and stored in block memory 210. More specifically, intrapredictor 216 generates an intra prediction signal by intra predictionwith reference to samples (for example, luma and/or chroma values) of ablock or blocks neighboring the current block, and then outputs theintra prediction signal to prediction controller 220.

Note that when an intra prediction mode in which a chroma block is intrapredicted from a luma block is selected, intra predictor 216 may predictthe chroma component of the current block based on the luma component ofthe current block.

Moreover, when information indicating the application of PDPC is parsedfrom an encoded bitstream, intra predictor 216 correctspost-intra-prediction pixel values based on horizontal/verticalreference pixel gradients.

[Inter Predictor]

Inter predictor 218 predicts the current block with reference to areference picture stored in frame memory 214. Inter prediction isperformed per current block or per sub-block (for example, per 4×4block) in the current block. For example, inter predictor 218 generatesan inter prediction signal of the current block or sub-block by motioncompensation by using motion information (for example, a motion vector)parsed from an encoded bitstream, and outputs the inter predictionsignal to prediction controller 220.

Note that when the information parsed from the encoded bitstreamindicates application of OBMC mode, inter predictor 218 generates theinter prediction signal using motion information for a neighboring blockin addition to motion information for the current block obtained frommotion estimation.

Moreover, when the information parsed from the encoded bitstreamindicates application of FRUC mode, inter predictor 218 derives motioninformation by performing motion estimation in accordance with thepattern matching method (bilateral matching or template matching) parsedfrom the encoded bitstream. Inter predictor 218 then performs motioncompensation using the derived motion information.

Moreover, when BIO mode is to be applied, inter predictor 218 derives amotion vector based on a model assuming uniform linear motion. Moreover,when the information parsed from the encoded bitstream indicates thataffine motion compensation prediction mode is to be applied, interpredictor 218 derives a motion vector of each sub-block based on motionvectors of neighboring blocks.

[Prediction Controller]

Prediction controller 220 selects either the intra prediction signal orthe inter prediction signal, and outputs the selected prediction signalto adder 208.

[Deblocking Filtering]

Next, deblocking filtering performed in encoder 100 and decoder 200configured as described above are described specifically with referenceto the drawings. It is to be noted that operations performed by loopfilter 120 included in encoder 100 are mainly described below, and loopfilter 212 included in decoder 200 performs similar operations.

As described above, when encoding an image, encoder 100 calculates aprediction error by subtracting, from an original signal, a predictionsignal which is generated by intra predictor 124 or inter predictor 126.Encoder 100 generates quantized coefficients by performing an orthogonaltransform process and a quantization process on a prediction error.Furthermore, encoder 100 restores the prediction error by performinginverse quantization and inverse orthogonal transform on the resultingquantized coefficients. Here, a quantization process is irreversibleprocessing, and thus the restored prediction error has an error(quantization error) from the pre-transform prediction error.

Deblocking filtering performed by loop filter 120 is a kind of filteringperformed with an aim to reduce the quantization error. Deblockingfiltering is applied to block boundaries to remove block noise. It is tobe noted that deblocking filtering is also simply referred to asfiltering hereinafter.

FIG. 11 is a flowchart indicating an example of deblocking filteringperformed by loop filter 120. For example, processing indicated in FIG.11 is performed for each of block boundaries.

First, loop filter 120 calculates a block boundary strength (Bs) inorder to determine a behavior of deblocking filtering (S101). Morespecifically, loop filter 120 determines a Bs using a prediction mode ofa block to be a target of a filter or a property of a motion vector. Forexample, Bs=2 is set when at least one of blocks across a boundary is anintra prediction block. In addition, Bs=1 is set when at least one ofthe following conditions (1) to (3) is satisfied: (1) at least one ofblocks across a boundary includes a higher orthogonal transformcoefficient; (2) the difference between motion vectors of both blocksacross a boundary is larger than or equal to a threshold value; and (3)the numbers of motion vectors or reference images of both blocks acrossa boundary are different from each other. Bs=0 is set when none of theconditions (1) to (3) is satisfied.

Next, loop filter 120 determines whether the set Bs is larger than afirst threshold value (S102). When Bs is smaller than or equal to thefirst threshold value (No in S102), loop filter 120 does not performfiltering (S107).

When the set Bs is larger than the first threshold value (Yes in S102),loop filter 120 calculates a pixel difference d in a boundary area,using pixel values of blocks located at both sides of a block boundary(S103). This processing is described with reference to FIG. 12 . Whenthe pixel values at the block boundary are defined as in FIG. 12 , loopfilter 120 calculates, for example,d=|p30−2×p20+p10|+|p33−2×p23+p13|+|q30−2×q20+g10|+|q33−2×q23+q13|.

Next, loop filter 120 determines whether the calculated d is larger thana second threshold value (S104). When the calculated d is smaller thanor equal to the second threshold value (No in S104), loop filter 120does not perform filtering (S107). It is to be noted that the firstthreshold value is different from the second threshold value.

When the calculated d is larger than the second threshold value (Yes inS104), loop filter 120 determines a filter characteristic (S105), andperforms filtering with the determined filter characteristic (S106). Forexample, a 5-tap filter of (1, 2, 2, 2, 1)/8 is used. Specifically, forp10 indicated in FIG. 12 , a calculation of(1×p30+2×p20+2×p10+2×q10+1×q20)/8 is performed. Here, in the filtering,clipping is performed so that variation falls within a certain rangewithout excessive smoothing. Clipping here is threshold processingwhich, for example, when a threshold value for clipping is tc and apixel value to be filtered is q, only allows the filtered pixel value totake a value within the range of q±tc.

Hereinafter, a description is given of an example of applying anasymmetrical filter across a block boundary in deblocking filteringperformed by loop filter 120 according to this embodiment.

FIG. 13 is a flowchart indicating an example of deblocking filteringaccording to this embodiment. It is to be noted that the processingindicated in FIG. 13 may be performed for each block boundary, or foreach unit of one or more pixels.

First, loop filter 120 obtains a coding parameter, and determines anasymmetrical filter characteristic across a boundary, using the obtainedcoding parameter (S111). In the present disclosure, the obtained codingparameter is assumed to, for example, characterize an errordistribution.

Here, filter characteristics are filter coefficients and parameters,etc. used to control filtering. In addition, a coding parameter may beany parameter which can be used to determine a filter characteristic. Acoding parameter may be information indicating an error per se, or maybe information or a parameter (which, for example, affects the magnitudeof the error) related to the error.

In addition, hereinafter, a pixel which has been determined to have alarge or small error based on a coding parameter, that is, a pixel whichis likely to have a large or small error is also simply referred to as apixel having a large or small error.

Here, a determination process does not need to be performed each time,and a process may be performed according to a predetermined rule whichassociates a coding parameter and a filter characteristic.

It is to be noted that, when each pixel is seen, even a pixel which isstatistically likely to have a small error may have an error larger thanan error of a pixel which is likely to have a large error.

Next, loop filter 120 executes filtering with the determined filtercharacteristic (S112).

Here, a filter characteristic determined in Step S111 does not alwaysneed to be asymmetrical, and can be designed to be symmetrical. It is tobe noted that, hereinafter, a filter having an asymmetrical filtercharacteristic across a block boundary is also referred to as anasymmetrical filter, and a filter having a symmetrical filtercharacteristic across a block boundary is also referred to as asymmetrical filter.

More specifically, the filter characteristic is determined consideringthe following two points that: a pixel determined to have a small erroris less affected by a neighboring pixel having a large error; and thepixel determined to have the large error is more affected by theneighboring pixel having the small error. In other words, the filtercharacteristic is determined such that a pixel having a larger error ismore affected by filtering. In other words, a filter characteristic isdetermined such that the pixel value of a pixel having a larger error ischanged by a larger amount before and after filtering. In this way, asfor a pixel which is likely to have a small error, it is possible toprevent the pixel from departing from a true value by a large change invalue. As for the pixel which is likely to have the large error, it ispossible to reduce the error of the pixel by changing the value afterbeing more affected by the pixel having the small error.

It is to be noted that an element which changes variation by a filer isdefined as a weight of a filter. In other words, a weight indicates adegree of influence of filtering on a current pixel. Increasing a weightmeans increasing influence of filtering on the pixel. In other words,increasing a weight means that a filtered pixel value is more affectedby another pixel. More specifically, increasing a weight meansdetermining a filter characteristic so that the pixel value of a pixelcan be changed by a larger amount before and after filtering, orfiltering is likely to be performed.

In other words, loop filter 120 increases the weight of a pixel having alarger error more significantly. It is to be noted that increasing theweight of a pixel having a larger error more significantly is notlimited to changing the weight continuously and includes changing theweight stepwise. In other words, it is only necessary that the weight ofa first pixel is smaller than the weight of a second pixel having alarger error than the first pixel. In addition, similar expressions arealso used below.

It is to be noted that a pixel having a larger error does not need tohave a larger weight in a finally determined filtering characteristic.In other words, for example, it is only necessary for loop filter 120 tochange a filter characteristic which becomes a reference determinedaccording to a conventional approach to have a tendency that a pixelhaving a larger error has a larger weight.

Hereinafter, a plurality of specific approaches for changing weightsasymmetrically are described. It is to be noted that any of theapproaches indicated below may be used, or a combination of a pluralityof approaches may be used.

As a first approach, loop filter 120 decreases a filter coefficient moresignificantly for a pixel having a larger error. For example, loopfilter 120 decreases a filter coefficient for a pixel having a largeerror, and increases a filter coefficient for a pixel having a smallerror.

For example, a description is given of an example of deblockingfiltering performed on pixel p1 indicated in FIG. 12 . This approach isnot applied hereinafter, and, for example, a filter determined accordingto a conventional approach is referred to as a reference filter. It isassumed that the reference filter is a 5-tap filter vertical to a blockboundary, and is set for (p3, p2, p1, q1, q2). In addition, a filtercoefficient is determined to be (1, 2, 2, 2, 1)/8. In addition, it isassumed that an error of block P is likely to be large, and that anerror of block Q is likely to be small. In this way, a filtercoefficient is set so that block P having a large error is more affectedby block Q having a small error. More specifically, a filter coefficientused for a pixel having a small error is set to be large, and a filtercoefficient used for a pixel having a large error is set to be small.For example, as a filter coefficient, (0.5, 1.0, 1.0, 2.0, 1.5)/6 isused.

As another example, 0 is used as a filter coefficient for a pixel havinga small error. For example, (0, 0, 1, 2, 2)/5 may be used as a filtercoefficient. In other words, a filter tap may be changed. A filtercoefficient which is currently 0 may be set to a value other than 0. Forexample, (1, 2, 2, 2, 1, 1)/9 may be used as a filter coefficient. Inother words, loop filter 120 may increase the number of filter taps at asmall error side.

It is to be noted that a reference filter is not a filter which ishorizontally symmetrical about a current pixel as in the case of (1, 2,2, 2, 1)/8 described above. In such a case, loop filter 120 furtheradjusts the filter. For example, the filter coefficient for a referencefilter to be used for a left-end pixel in block Q is (1, 2, 3, 4, 5)/15,and the filter coefficient for a reference filter to be used for aright-end pixel in block P is (5, 4, 3, 2, 1)/15. In other words, inthis case, the reverse-landscape filter coefficients are used betweenthe pixels across the block boundary. Such a filter characteristic whichis reverse-symmetrical across a block boundary can be said to be “afilter characteristic which is symmetrical across a block boundary”. Inother words, a filter characteristic which is asymmetrical across ablock boundary is a filter characteristic which is notreverse-symmetrical across a block boundary.

In addition, similarly to the above, when block P has a large error andblock Q has a small error, loop filter 120 changes, for example, (5, 4,3, 2, 1)/15 which is the filter coefficient for a reference filter to beused for a right-end pixel in block P to (2.5, 2.0, 1.5, 2.0, 1.0)/9.

In this way, in deblocking filtering, a filter having filtercoefficients which change asymmetrically across a block boundary areused. For example, loop filter 120 determines a reference filter havingfilter coefficients which are symmetrical across a boundary according toa predetermined reference. Loop filter 120 changes the reference filterto have filter coefficients which are asymmetrical across a boundary.More specifically, loop filter 120 performs at least one of; increasinga filter coefficient of at least one pixel having a small error amongthe filter coefficients of the reference filter; and decreasing a filtercoefficient of at least one pixel having a large error among the filtercoefficients of the reference filter.

Next, a second approach for changing weights asymmetrically isdescribed. First, loop filter 120 performs a filter calculation using areference filter. Next, loop filter 120 performs asymmetrical weightingacross a block boundary onto reference change amount Δ0 which is theamount of change in pixel value before and after the filter calculationusing a reference filter. It is to be noted that, hereinafter, fordistinction, processing using a reference filter is referred to as afilter calculation, and sequential processing including a filtercalculation and subsequent correction (for example, asymmetricalweighting) is referred to as filtering (deblocking filtering).

For example, in the case of a pixel having a small error, loop filter120 calculates corrected change amount Δ0 by multiplying referencechange amount Δ0 with a coefficient smaller than 1. In addition, in thecase of a pixel having a large error, loop filter 120 calculates acorrected change amount Δ0 by multiplying reference change amount Δ0with a coefficient larger than 1. Next, loop filter 120 generates afiltered pixel value by adding a pixel value before a filter calculationto corrected change amount Δ1. It is to be noted that loop filter 120may perform only one of processing on the pixel having a small error andprocessing on the pixel having a large error.

For example, similarly to the above, it is assumed that block P has alarge error and block Q has a small error. In this case, in the case ofa pixel included in block Q having a small error, loop filter 120calculates corrected change amount Δ1 by, for example, multiplyingreference change amount Δ0 by 0.8. In addition, in the case of a pixelincluded in block P having a large error, loop filter 120 calculatescorrected change amount Δ1 by, for example, multiplying reference changeamount Δ0 by 1.2. In this way, it is possible to decrease variation inpixel value having a small error. In addition, it is possible toincrease variation in pixel value having a large error.

It is to be noted that 1:1 may be selected as a ratio between acoefficient that is multiplied with reference change amount Δ0 of apixel having a small error and a coefficient that is multiplied withreference change amount Δ0 having a large error. In this case, thefilter characteristic is symmetrical across a block boundary.

In addition, loop filter 120 may calculate a coefficient that ismultiplied with reference change amount Δ0 by multiplying the referencecoefficient by a constant. In this case, loop filter 120 uses a largerconstant for a pixel having a large error than a constant for a pixelhaving a small error. As a result, the change amount in pixel value ofthe pixel having the large error increases, and the change amount inpixel value of the pixel having the small error decreases. For example,loop filter 120 uses 1.2 or 0.8 as a constant for a pixel that neighborsa block boundary, and uses 1.1 or 0.9 as a constant for a pixel that isapart by one pixel from the pixel that neighbors the block boundary. Inaddition, a reference coefficient is calculated according to, forexample, (A×(q1−p1)−B×(q2−p2)+C)/D. Here, A, B, C, and D are constants.For example, A=9, B=3, C=8, and D=16 are satisfied. In addition, p1, p2,q1, and q2 are pixel values of pixels located across a block boundaryand are in a positional relationship indicated in FIG. 12 .

Next, a third approach for changing weights asymmetrically is described.Loop filter 120 performs a filter calculation using a filter coefficientof a reference filter similarly to the second approach. Next, loopfilter 120 adds asymmetrical offset values to pixel values after beingsubjected to the filter calculation across a block boundary. Morespecifically, loop filter 120 adds a positive offset value to a pixelvalue of a pixel having a large error so that the value of the pixelhaving the large error is made closer to the value of pixel which islikely to have a small error and the variation of the pixel having thelarge error becomes large. In addition, loop filter 120 adds a negativeoffset value to the pixel value of the pixel having the small error sothat the value of the pixel having the small error is not made closer tothe value of the pixel having the large error and the variation of thepixel having the small error becomes small. As a result, the changeamount in pixel value of the pixel having the large error increases, andthe change amount in pixel value of the pixel having the small errordecreases. It is to be noted that loop filter 120 may perform only oneof processing on the pixel having a small error and processing on thepixel having a large error.

For example, for a pixel included in a block having a large error, loopfilter 120 calculates corrected change amount Δ1 by adding a positiveoffset value (for example, 1) to the absolute value of reference changeamount Δ0. In addition, for a pixel included in a block having a smallerror, loop filter 120 calculates corrected change amount Δ1 by adding anegative offset value (for example, −1) to the absolute value ofreference change amount Δ0. Next, loop filter 120 generates a filteredpixel value by adding corrected change amount Δ1 to the pixel valuebefore being subjected to the filter calculation. It is to be noted thatloop filter 120 may add an offset value to the filtered pixel valueinstead of adding an offset value to a change amount. In addition, theoffset values may not be symmetrical across a block boundary.

In addition, when a filter tap is set for a plurality of pixelsneighboring a block boundary, loop filter 120 may change only theweights for particular pixels or may change the weights for all thepixels. In addition, loop filter 120 may change the weights of thetarget pixels according to the distances from the block boundary to thetarget pixels. For example, loop filter 120 may make filter coefficientsfor two pixels from a block boundary asymmetrical, and make the otherfilter coefficients for subsequent pixels symmetrical. In addition,filter weights may be common to a plurality of pixels, or may be set foreach pixel.

Next, a fourth approach for changing weights asymmetrically isdescribed. Loop filter 120 performs a filter calculation using a filtercoefficient of a reference filter. Next, when a change amount Δ in pixelvalue before and after the filter calculation exceeds a clip width whichis a reference value, loop filter 120 clips the change amount Δ to theclip width. Loop filter 120 sets asymmetrical clip widths across a blockboundary.

Specifically, loop filter 120 makes a clip width for a pixel having alarge error wider than the clip width of a pixel having a small error.For example, loop filter 120 makes the clip width for the pixel havingthe large error to a constant multiple of the clip width for the pixelhaving the smaller error. As a result of changing the clip width, thevalue of the pixel having the small error is prohibited from changingsignificantly. In addition, the value of the pixel having the largeerror is allowed to change significantly.

It is to be noted that loop filter 120 may adjust the absolute values ofthe clip widths instead of specifying a clip width ratio. For example,loop filter 120 fixes the clip width for a pixel having a large error ata multiple of a predetermined reference clip width. Loop filter 120 setsthe ratio between the clip width for the pixel having the large errorand the clip width for a pixel having a small error to 1.2:0.8.Specifically, for example, it is assumed that the reference clip widthis 10, and that the change amount Δ before and after a filtercalculation is 12. In this case, in the case where the reference clipwidth is used as it is, the change amount Δ is corrected to 10 bythreshold processing. In the opposite case where a target pixel is apixel having a large error, the reference clip width is multiplied by,for example, 1.5. In this way, since the clip width becomes 15, nothreshold processing is performed, and the change amount Δ is 12.

Next, a fifth approach for changing weights asymmetrically is described.Loop filter 120 sets an asymmetrical condition for determining whetherto perform filtering across a block boundary. Here, the condition fordetermining whether to perform filtering is, for example, a firstthreshold value or a second threshold value indicated in FIG. 11 .

More specifically, loop filter 120 sets a condition for increasing thelikeliness of filtering on a pixel having a large error and a conditionfor decreasing the likeliness of filtering on a pixel having a smallerror. For example, loop filter 120 sets a higher threshold value for apixel having a small error than a threshold value for a pixel having alarge error. For example, loop filter 120 sets the threshold value forthe pixel having the small error to be a constant multiple of thethreshold value for the pixel having the large error.

In addition, loop filter 120 may adjust the absolute values of thethreshold values not only specifying the threshold value ratio. Forexample, loop filter 120 may fix a threshold value for a pixel having asmall error to a multiple of a predetermined reference threshold value,and may set the ratio between the threshold value for the pixel havingthe small error and a threshold value for a pixel having a large errorto be 1.2:0.8.

Specifically, it is assumed that a reference threshold value for asecond threshold value in Step S104 is 10, and that the d calculatedfrom the pixel value in a block is 12. In the case where the referencethreshold value is used as the second threshold value as it is, it isdetermined that filtering is performed. In the opposite case where atarget pixel is a pixel having a small error, for example, a valueobtained by multiplying the reference threshold value by 1.5 is used asthe second threshold value. In this case, the second threshold valuebecomes 15 which is larger than d. In this way, it is determined that nofiltering is performed.

In addition, constants, etc. indicating weights based on errors used inthe above-described first to fifth approaches may be valuespredetermined in encoder 100 and decoder 200, or may be variable.Specifically, these constants include: a filter coefficient or acoefficient that is multiplied with a filter coefficient of a referencefilter in the first approach; a coefficient that is multiplied withreference change amount Δ0 or a constant that is multiplied with areference coefficient in the second approach; an offset value in thesecond approach; a clip width or a constant multiplied with a referenceclip width in the fourth approach; and a threshold value or a constantthat is multiplied with a reference threshold value in the fifthapproach.

When a constant is variable, information indicating the constant may beincluded in a bitstream as a parameter in units of a sequence or aslice, and may be transmitted from encoder 100 to decoder 200. It is tobe noted that the information indicating the constant may be informationindicating the constant as it is, or may be information indicating aratio with or a difference from a reference value.

In addition, according to errors, as methods for changing coefficientsor constants, for example, there are a method for changing themlinearly, a method for changing them quadratically, a method forchanging them exponentially, a method using a look-up table indicatingthe relationships between errors and constants, or other methods.

In addition, when an error is larger than or equal to a reference, orwhen an error is smaller than or equal to a reference, a fixed value maybe used as a constant. For example, loop filter 120 may set a variableto a first value when an error is below a predetermined range, may set avariable to a second value when an error is above the predeterminedrange, or may change a variable to a continuous variable according to anerror, in a range from the first value to the second value when theerror is within the predetermined range.

In addition, when an error exceeds a predetermined reference, loopfilter 120 may use a symmetrical filter (reference filter) without usingan asymmetrical filter.

In addition, in the case of using a look-up table, etc, loop filter 120may hold tables for both a case where an error is large and a case wherean error is small, or may hold only one of the tables and may calculatea constant for the other according to a rule predetermined based on thecontent of the table.

As described above, encoder 100 and decoder 200 according to thisembodiment are capable of reducing errors in a reconstructed image byusing an asymmetrical filter, and thereby increasing coding efficiency.

Embodiment 2

Embodiments 2 to 6 describe specific examples of coding parameters whichcharacterize the above-described error distributions. In thisembodiment, loop filter 120 determines a filter characteristic accordingto the position of a current pixel in a block.

FIG. 14 is a flowchart indicating an example of deblocking filteringaccording to this embodiment. First, loop filter 120 obtains informationindicating the position of the current pixel in a block, as a codingparameter which characterizes an error distribution. Loop filter 120determines an asymmetrical filter characteristic across a block boundarybased on the position (S121).

Next, loop filter 120 executes filtering with the determined filtercharacteristic (S122).

Here, a pixel distant from a reference pixel in intra prediction islikely to have a large error than a pixel close to the reference pixelin intra prediction. Accordingly, loop filter 120 determines the filtercharacteristic so that the pixel value of the pixel more distant fromthe reference pixel in intra prediction changes by a larger changeamount before and after filtering.

For example, in the case of H.265/HEVC or JEM, as indicated in FIG. 15 ,a pixel close to a reference pixel is a pixel present at an upper-leftpart of a block, and a pixel distant from a reference pixel is a pixelpresent at a lower-right part of the block. Accordingly, loop filter 120determines the filter characteristic so that the weight for thelower-right pixel in the block becomes larger than the weight for theupper-left pixel.

Specifically, loop filter 120 determines the filter characteristic sothat the pixel distant from the reference pixel in intra prediction ismore affected by filtering as described in Embodiment 1. In other words,loop filter 120 increases the weight for the pixel distant from thereference pixel in intra prediction. Here, as described above,increasing a weight is performing at least one of: (1) decreasing afilter coefficient; (2) increasing a filter coefficient for a pixelacross a boundary (that is, a pixel close to a reference pixel in intraprediction); (3) increasing a coefficient which is multiplied with achange amount; (4) increasing an offset value for a change amount; (5)increasing a clip width; and (6) changing a threshold value so as toincrease the likeliness of filtering. As for the pixel close to thereference pixel in intra prediction, loop filter 120 determines a filtercharacteristic so that the pixel is less affected by filtering. In otherwords, loop filter 120 decreases the weight for the pixel close to thereference pixel in intra prediction. Here, as described above,decreasing a weight is performing at least one of: (1) increasing afilter coefficient; (2) decreasing a filter coefficient for a pixelacross a boundary (that is, a pixel close to a reference pixel in intraprediction); (3) decreasing a coefficient which is multiplied with achange amount; (4) decreasing an offset value for a change amount; (5)decreasing a clip width; and (6) changing a threshold value so as todecrease the likeliness of filtering.

It is to be noted that the above processing may be performed when intraprediction is used, and may not by performed for a block for which interprediction is used. However, since the property of an intra predictionblock may have an influence in inter prediction, the above-describedprocessing may be performed also on an inter prediction block.

In addition, loop filter 120 may change weights by arbitrarilyspecifying positions in a particular block. For example, loop filter 120may increase the weight of a lower-right pixel in a block and decreasethe weight of an upper-left pixel in the block as described above. It isto be noted that loop filter 120 may change weights by arbitrarilyspecifying positions other than the upper-left and lower-right positionsin the particular block.

In addition, as indicated in FIG. 15 , left-side blocks have a largeerror and right-side blocks have a small error at the boundaries ofhorizontally neighboring blocks. Thus, loop filter 120 may increase theweights for the left-side blocks and decrease the weights for theright-side blocks at the boundaries of horizontally neighboring blocks.

Likewise, at the boundaries of vertically neighboring blocks, upper-sideblocks have a large error, and lower-side blocks have a small error.Thus, loop filter 120 may increase the weights for the upper-side blocksand decrease the weights for the lower-side blocks at the boundaries ofvertically neighboring blocks.

In addition, loop filter 120 may change weights according to thedistances from a reference pixel in intra prediction. In addition, loopfilter 120 may determine weights in units of a block boundary, or maydetermine weights in units of a pixel. Errors are likely to be largewith increase in distance from a reference pixel. Thus, loop filter 120determines a filter characteristic so that the gradient of weightsbecomes sharp with increase in distance from the reference pixel. Inaddition, loop filter 120 determines the filter characteristic so thatthe weight gradient in the upper side of the right side of a block isgentler than the weight gradient in the lower side thereof.

Embodiment 3

In this embodiment, loop filter 120 determines a filter characteristicaccording to an orthogonal transform basis.

FIG. 16 is a flowchart indicating an example of deblocking filteringaccording to this embodiment. First, loop filter 120 obtains informationindicating orthogonal transform basis used for a current block, as acoding parameter which characterizes an error distribution. Loop filter120 determines an asymmetrical filter characteristic across a blockboundary based on the orthogonal transform basis (S131).

Next, loop filter 120 executes filtering with the determined filtercharacteristic (S132).

Encoder 100 selects an orthogonal transform basis which is a transformbasis at the time when orthogonal transform is performed, from aplurality of candidates. The plurality of candidates include, forexample, a flat basis whose zero-order transform basis is flat such asDCT-II, or the like, and a basis whose zero-order transform basis is notflat such as DST-VII, or the like. FIG. 17 is a diagram indicating aDCT-II transform basis. FIG. 18 is a diagram indicating a DCT-VIItransform basis.

The zero-order basis in DCT-II is constant regardless of the positionsin a block. In other words, when DCT-II is used, errors in the blocksare constant. Thus, when both blocks across a block boundary have beentransformed using DCT-II, loop filter 120 performs filtering using asymmetrical filter without using an asymmetrical filter.

In contrast, the value of the zero-order basis in DST-VII becomes largewith increase in distance from a left or upper block boundary. In otherwords, errors are likely to be large with increase in distance from theleft or upper block boundary. Thus, loop filter 120 uses an asymmetricalfilter when at least one of the two blocks across a block boundary hasbeen transformed using DST-VII. Specifically, loop filter 120 determinesa filter characteristic so that a pixel having a smaller value of alower-order (for example, zero-order) basis in a block is less affectedby filtering.

More specifically, when both blocks across a block boundary have beentransformed using DST-VII, loop filter 120 determines the filtercharacteristic so that a lower-right pixel in the block is more affectedby filtering according to the above-described approach. In addition,loop filter 120 determines the filter characteristic so that anupper-left pixel in the block is less affected by filtering.

In addition, also when a block for which DST-VII has been used and ablock for which DCT-II has been used neighbor vertically, loop filter120 determines a filter characteristic so that a filter weight for apixel in the lower part of the upper block for which DST-VII has beenused and which neighbors a block boundary becomes larger than a filterweight for a pixel in the upper part of the lower block for which DCT-IIhas been used and which neighbors the block boundary. However, thedifference in the amplitude of a low-order basis in this case is smallerthan the difference in the amplitude of the lower-order basis whenblocks for which DST-VII has been used neighbor each other. Thus, loopfilter 120 sets a filter characteristic so that the weight gradient inthis case becomes smaller than the weight gradient in the case whereblocks for which DST-VII has been used neighbor each other. For example,loop filter 120 sets the weights in the case where a block for whichDCT-II has been used and a block for which DCT-II has been used neighborvertically to 1:1 (a symmetrical filter), the weights in the case wherea block for which DST-VII has been used and a block for which DST-VIIhas been used neighbor vertically to 1.3:0.7, and the weights in thecase where a block for which DST-VII has been used and a block for whichDCT-II has been used neighbor vertically to 1.2:0.8.

Embodiment 4

In this embodiment, loop filter 120 determines a filter characteristicaccording to the pixel values of pixels across a block boundary.

FIG. 19 is a flowchart indicating an example of deblocking filteringaccording to this embodiment. First, loop filter 120 obtains informationindicating the pixel values of pixels in blocks across a boundary, as acoding parameter which characterizes an error distribution. Loop filter120 determines an asymmetrical filter characteristic across the blockboundary based on the pixel values (S141).

Next, loop filter 120 executes filtering with the determined filtercharacteristic (S142).

For example, loop filter 120 increases the difference in filtercharacteristic across a block boundary with increase in difference d0 inpixel value. Specifically, loop filter 120 determines a filtercharacteristic so that the difference in influence by filtering becomeslarge. For example, loop filter 120 sets weights to 1.4:0.6 whend0>(quantization parameter)×(constant) is satisfied, and sets weights to1.2:0.8 when d0>(quantization parameter)×(constant) is not satisfied. Inother words, loop filter 120 compares difference d0 in pixel value and athreshold value based on a quantization parameter, and when differenced0 in pixel value is larger than the threshold value, increases thedifference in filter characteristic across the block boundary so thatthe difference becomes larger than when difference d0 in pixel value issmaller than the threshold value.

As another example, loop filter 120 increases the difference in filtercharacteristic across a block boundary with increase in average value b0of variance in pixel value in both blocks across the boundary.Specifically, loop filter 120 may determine a filter characteristic sothat the difference in influence by filtering becomes large. Forexample, loop filter 120 sets weights to 1.4:0.6 when b0>(quantizationparameter)×(constant) is satisfied, and sets weights to 1.2:0.8 whenb0>(quantization parameter)×(constant) is not satisfied. In other words,loop filter 120 compares variance b0 in pixel value and a thresholdvalue based on a quantization parameter, and when variance b0 in pixelvalue is larger than the threshold value, increases the difference infilter characteristic across the block boundary so that the differencebecomes larger than when variance b0 in pixel value is smaller than thethreshold value.

It is to be noted that the block whose weight is to be increased amongneighboring blocks, that is, the block having a larger error can beidentified according to the approach of Embodiment 2 or 3 describedabove or approaches, etc. according to Embodiment 6 to be describedlater. In other words, loop filter 120 determines an asymmetrical filtercharacteristic across a block boundary according to a predetermined rule(for example, the approach according to Embodiment 2, 3, or 6). Next,loop filter 120 changes the determined filter characteristic so that thedifference in filter characteristic across the block boundary becomeslarge based on difference d0 in pixel values. In other words, loopfilter 120 increases the ratio or difference between the weight for apixel having a large error and the weight for a pixel having a smallerror.

Here, when difference d0 in pixel value is large, there is a possibilitythat a block boundary coincides with the edge of an object in an image.In such a case, it is possible to reduce unnecessary smoothing bydecreasing the difference in filter characteristic across the blockboundary.

On the contrary, it is to be noted that loop filter 120 may decrease thedifference in filter characteristic across the block boundary withincrease in difference d0 in pixel value. Specifically, loop filter 120determines a filter characteristic so that the difference in influenceby filtering becomes small. For example, loop filter 120 sets weights to1.2:0.8 when d0>(quantization parameter)×(constant) is satisfied, andsets weights to 1.4:0.6 when d0>(quantization parameter)×(constant) isnot satisfied. It is to be noted that the weights may be set to 1:1(symmetrical filter) when the above relationship is satisfied. In otherwords, loop filter 120 compares difference d0 in pixel value and athreshold value based on a quantization parameter, and when differenced0 in pixel value is larger than the threshold value, decreases thedifference in filter characteristic across the block boundary so thatthe difference becomes smaller than when difference d0 in pixel value issmaller than the threshold value.

For example, when difference d0 in pixel value is large, a blockboundary tends to be noticeable. In such a case, it is possible toreduce weakening of smoothing by an asymmetrical filter by decreasingthe difference in filter characteristic across the block boundary.

It is to be noted that these two processes may be performed at the sametime. For example, loop filter 120 may use a first weight whendifference d0 in pixel value is less than a first threshold value, usesa second weight for a larger difference than the difference for whichthe first weight is used, when difference d0 in pixel value is largerthan or equal to the first threshold value and less than the secondthreshold value, and uses a third weight for a smaller difference thanthe difference for which the second weight is used, when difference d0in pixel value is larger than or equal to the second threshold value.

In addition, difference d0 in pixel value may be the difference per sebetween pixel values of pixels across a boundary, or the average orvariance of the differences between the pixel values of the pixels. Forexample, difference d0 in pixel value is calculated according to(A×(q1−p1)−B×(q2−p2)+C)/D. Here, A, B, C, and D are constants. Forexample, A=9, B=3, C=8, and D=16 are satisfied. In addition, p1, p2, q1,and q2 are pixel values of pixels located across a block boundary andare in a positional relationship indicated in FIG. 12 .

It is to be noted that difference d0 in pixel value and weights forpixels may be set in units of a pixel, in units of a block boundary, orin units of a block group including a plurality of blocks (for example,in units of a largest coding unit (LCU)).

Embodiment 5

In this embodiment, loop filter 120 determines a filter characteristicaccording to an intra prediction direction and a block boundarydirection.

FIG. 20 is a flowchart indicating an example of deblocking filteringaccording to this embodiment. First, loop filter 120 obtains informationindicating an angle between the intra prediction direction and the blockboundary, as a coding parameter which characterizes an errordistribution. Loop filter 120 determines an asymmetrical filtercharacteristic across a block boundary, based on the angle (S151).

Next, loop filter 120 executes filtering with the determined filtercharacteristic (S152).

Specifically, loop filter 120 increases the difference in filtercharacteristic across a block boundary more significantly as the angleis closer to the vertical axis, and decreases the difference in filtercharacteristic across a block boundary more significantly as the angleis closer to the horizontal axis. More specifically, loop filter 120determines the filter characteristic so that the difference betweenfilter weights for pixels at both sides across a block boundary becomeslarge when the intra prediction direction is close to the vertical axisrelative to the block boundary, and the difference between filterweights for pixels at both sides across a block boundary becomes smallwhen the intra prediction direction is close to the horizontal axisrelative to the block boundary. FIG. 21 is a diagram indicating examplesof weights for relationships between intra prediction directions andblock boundary directions.

It is to be noted that the block whose weight is to be increased amongneighboring blocks, that is, the block having a larger error can beidentified according to the approach of Embodiment 2 or 3 describedabove or approaches, etc. according to Embodiment 6 to be describedlater. In other words, loop filter 120 determines an asymmetrical filtercharacteristic across a block boundary according to a predetermined rule(for example, the approach according to Embodiment 2, 3, or 6). Next,loop filter 120 changes the determined filter characteristic so that thedifference in filter characteristic across the block boundary becomeslarge based on the intra prediction direction and the block boundarydirection.

In addition, encoder 100 and decoder 200 identify the intra predictiondirection using, for example, an intra prediction mode.

It is to be noted that when the intra prediction mode is Planner mode orDC mode, loop filter 120 does not always need to consider the blockboundary direction. For example, when the intra prediction mode isPlanar mode or DC mode, loop filter 120 may use a predetermined weightor the difference in weight regardless of the block boundary direction.Alternatively, loop filter 120 may use a symmetrical filter when theintra prediction mode is Planar mode or DC mode.

Embodiment 6

In this embodiment, loop filter 120 determines a filter characteristicaccording to a quantization parameter indicating a quantization width.

FIG. 22 is a flowchart indicating an example of deblocking filteringaccording to this embodiment. First, loop filter 120 obtains informationindicating the quantization parameter used in the quantization of acurrent block, as a coding parameter which characterizes an errordistribution. Loop filter 120 determines an asymmetrical filtercharacteristic across a block boundary, based on the quantizationparameter (S161).

Next, loop filter 120 executes filtering with the determined filtercharacteristic (S162).

Here, an error is likely to be large when a quantization parameter islarger. Thus, loop filter 120 determines a filter characteristic so thatinfluence of filtering becomes large as the quantization parameterbecomes larger.

FIG. 23 is a diagram indicating an example of weights for quantizationparameters. As shown in FIG. 23 , loop filter 120 increases the weightfor the upper-left pixel in a block with increasing quantizationparameter. On the contrary, loop filter 120 decreases the weight for thelower-right pixel in the block with increasing quantization parameter.In other words, loop filter 120 determines a filter characteristic sothat change in influence of filtering with changing quantizationparameter for the upper-left pixel becomes larger than change ininfluence of filtering with changing quantization parameter for thelower-right pixel.

Here, the upper-left pixel in the block is more likely to be affected bya quantization parameter than the lower-right pixel in the block. Thus,it is possible to reduce errors appropriately by performing theprocessing as described above.

In addition, loop filter 120 may determine, for each of two blocksacross a boundary, a weight for the block based on the quantizationparameter for the block, or may calculate an average value ofquantization parameters for the two blocks and determine weights for thetwo blocks based on the average value. Alternatively, loop filter 120may determine weights for the two blocks based on the quantizationparameter for one of the blocks. For example, loop filter 120 determinesa weight for the one block based on the quantization parameter for theblock using the above-described approach. Next, based on the determinedweight, loop filter 120 determines a weight for the other blockaccording to a predetermined rule.

In addition, loop filter 120 may use a symmetrical filter when thequantization parameters for the two blocks are different or when thedifference between the quantization parameters for the two blocksexceeds a threshold value.

In addition, in FIG. 23 , although weights are set using a linearfunction, but an arbitrary function other than the linear function or atable may be used. For example, a curve indicating the relationshipsbetween quantization parameters and quantization steps (quantizationwidths) may be used.

In addition, loop filter 20 may use a symmetrical filter without usingan asymmetrical filter when a quantization parameter exceeds a thresholdvalue.

In addition, when a quantization parameter is described at a decimalaccuracy, loop filter 120 may perform a calculation that is, forexample, a round-off, a round-up, a cut-off, or the like onto thequantization parameter and use the quantization parameter after beingsubjected to the calculation in the above-described processing.Alternatively, loop filter 120 may perform the processing taking intoaccount the decimal point level.

Although the plurality of approaches for determining errors have beendescribed in Embodiments 2 to 6, two or more of these approaches may becombined. In this case, loop filter 120 may perform weighting oncombined two or more elements.

Hereinafter, a variation is described.

Examples other than the examples of coding parameters described abovemay be used. For example, coding parameters may be the kind oforthogonal transform (such as Wavelet, DFT, lapped transform, or thelike), a block size (the width and height of a block), a motion vectordirection, the length of a motion vector, the number of referencepictures which are used in inter prediction, and information indicatinga reference filter characteristic. Alternatively, these parameters maybe used in combination. For example, loop filter 120 may use anasymmetrical filter only when the length of a block boundary correspondsto 16 pixels or less and a current pixel to be filtered is close to areference pixel in intra prediction, and may use a symmetrical filter inthe other cases. As another example, asymmetrical processing may beperformed only when a filter of a predetermined type among a pluralityof filter candidates has been used. For example, an asymmetricalprocessing may be used only when a variation by a reference filter iscalculated according to (A×(q1−p1)−B×(q2−p2)+C)/D. Here, A, B, C, and Dare constants. For example, A=9, B=3, C=8, and D=16 are satisfied. Inaddition, p1, p2, q1, and q2 are pixel values of pixels located across ablock boundary and are in a positional relationship indicated in FIG. 12.

In addition, loop filter 120 may perform the processing on only one of aluminance signal and a chrominance signal or on the both. In addition,loop filter 120 may perform common processing or different processing onthe luminance signal and the chrominance signal. For example, loopfilter 120 may use different weights for the luminance signal and thechrominance signal, or may determine weights according to differentrules.

In addition, various kinds of parameters for use in the above processingmay be determined by encoder 100, or may be preset fixed values.

In addition, whether to perform the above processing or the details ofthe processing may be switched based on a predetermined unit. Examplesof the predetermined unit include a slice unit, a tile unit, a wavefrontdividing unit, or a CTU unit. In addition, the details of the processingare which one of the plurality of approaches described above is used, orparameters indicating weights, etc., or parameters for determiningthese.

In addition, loop filter 120 may limit the area in which the aboveprocessing are performed to a CTU boundary, a slice boundary, or a tileboundary.

In addition, the number of filter taps may vary between a symmetricalfilter and an asymmetrical filter.

In addition, loop filter 120 may change whether to perform the aboveprocessing or the details of the processing according to a frame type(I-frame, P-frame, or B-frame).

In addition, loop filter 120 may determine whether to perform theprocessing or the details of the processing according to whetherparticular processing at a pre-stage or a post-stage has been performed.

In addition, loop filter 120 may perform different processing accordingto the kind of the prediction mode used for a block, or may perform theabove processing only on a block for which a particular prediction modeis used. For example, loop filter 120 may perform different processingbetween a block for which intra prediction is used, a block for whichinter prediction is used, and a merged block.

In addition, encoder 100 may encode filter information which isparameters indicating whether to perform the above processing or thedetails of the processing. In other words, encoder 100 may generate anencoded bitstream including filter information. This filter informationmay include information indicating whether to perform the aboveprocessing on a luminance signal, information indicating whether toperform the above processing on a chrominance signal, informationindicating whether to change processing according to respectiveprediction modes, or other information.

In addition, decoder 200 may perform the above processing based onfilter information included in an encoded bitstream. For example,decoder 200 may determine whether to perform the above processing or thedetails of the processing, based on the filter information.

Embodiment 7

In this embodiment, loop filter 120 determines a filter characteristicaccording to an orthogonal transform basis, as in Embodiment 3 describedabove. It is to be noted that this embodiment indicates theconfiguration and processing in Embodiment 3 described above morespecifically, and particularly describes the configuration andprocessing for determining a filter characteristic according tocombinations of orthogonal transform bases of mutually neighboringblocks. In addition, loop filter 212 in decoder 200 is configuredsimilarly to loop filter 120 of encoder 100, and performs processingoperation similar to that of loop filter 120. Accordingly, in thisembodiment, the configuration and processing operation of loop filter120 of encoder 100 is described, and the configuration and processingoperation of loop filter 212 of decoder 200 is not described in detail.

Various orthogonal transform bases are used for orthogonal transformwhich is used in image encoding. For this reason, an error distributionmay not be spatially uniform. It is to be noted that an orthogonaltransform basis is also referred to as a transform basis, or simply as abasis.

Specifically, in image encoding, a residual between a prediction signaland an original signal which is generated by inter prediction or intraprediction is orthogonal-transformed, and quantized. In this way, theamount of data is reduced. Quantization is irreversible processing, andthus encoded image includes differences from a pre-encoding image, thatis, errors.

However, an error distribution caused by encoding is not alwaysspatially uniform even with the use of a constant quantizationparameter. The error distribution is considered to depend on orthogonaltransform bases.

In other words, transformer 106 selects a transform basis at the time ofperforming orthogonal transform from a plurality of candidates. At thistime, for example, a DCT-II basis may be selected as a basis whosezero-order transform basis is flat, and a DST-VII basis may be selectedas a basis whose zero-order transform basis is not flat.

FIG. 24 is a diagram indicating DCT-II which is an example of a basis.It is to be noted that the horizontal axis of the graph in FIG. 24indicates positions on a one-dimensional space, and the vertical axisthereof indicates basis values (that is, amplitudes). Here, k denotes abasis order, n denotes a position on the one-dimensional space, and Ndenotes the number of pixels to be orthogonal-transformed. It is to benoted that position n on the one-dimensional space is a position in thehorizontal direction or a position in the vertical direction, and thatthe values of n increase from left to right in the horizontal directionand from top to bottom in the vertical direction. Furthermore, x_(n)denotes the pixel value (specifically, a residual) of a pixel atposition n, and Xk denotes a result of frequency transform in the k-thorder, that is a transform coefficient.

In DCT-II, transform coefficient Xo is indicated according to Expression(3) below when k=0 is satisfied.

$\begin{matrix}\left\lbrack {{Math}.\mspace{14mu} 3} \right\rbrack & \; \\{X_{0} = {\sqrt{\frac{2}{N}} \cdot \sqrt{\frac{1}{2}}}} & (3)\end{matrix}$

In DCT-II, transform coefficient Xk is indicated according to Expression(4) below when 1≤k≤N−1 is satisfied.

$\begin{matrix}\left\lbrack \left\lbrack {{Math}.\mspace{14mu} 4} \right\rbrack \right. & \; \\{X_{k} = {\sqrt{\frac{2}{N}} \cdot {\sum\limits_{n = 0}^{N - 1}\;{{ϰ_{n} \cdot \;\cos}\;\left\{ {\frac{\pi}{N}\left( {n + \frac{1}{2}} \right)k} \right\}}}}} & (4)\end{matrix}$

FIG. 25 is a diagram indicating DST-VII which is an example of a basis.It is to be noted that the horizontal axis in FIG. 25 indicatespositions on a one-dimensional space, and the vertical axis thereofindicates basis values (that is, amplitudes).

In DST-VII, transform coefficient Xk is indicated according toExpression (5) below when 0≤k≤N−1 is satisfied.

$\begin{matrix}\left\lbrack \left\lbrack {{Math}.\mspace{14mu} 5} \right\rbrack \right. & \; \\{X_{k} = {\sqrt{\frac{2}{N + \frac{1}{2}}} \cdot {\sum\limits_{n = 0}^{N - 1}\;{{ϰ_{n} \cdot \;\sin}\;\left\{ {\frac{\pi}{N + \frac{1}{2}}\left( {n + 1} \right)\left( {k + \frac{1}{2}} \right)} \right\}}}}} & (5)\end{matrix}$

In this way, a transform coefficient is basically determined accordingto Σ (pixel value×transform basis). In addition, a transform coefficientfor a lower-order basis is likely to be larger than a transformcoefficient for a higher-order basis. For this reason, if a DST-VIIbasis whose zero-order basis is not flat is used as a transform basis,deviation occurs in an error distribution according to the values of alow-order bases (that is, amplitudes) even if the same amount ofquantization errors are added to transform coefficients. In other words,in a block, in an upper-side or left-side area in which the value of alow-order basis is small is likely to have a small error, and, on thecontrary, in the block, in a lower-side or right-side area in which thevalue of a low-order basis is large is likely to have a large error.

FIG. 26 is a diagram indicating error distributions of four neighboringblocks and deblocking-filtered error distributions of the fourneighboring blocks.

As indicated in the left sides of (a) and (b) in FIG. 26 , when DST-VIIis used for orthogonal transform of the respective four blocks, errorsare small in the upper-side or left-side areas in these blocks, and, onthe contrary, errors are large in the lower-side or right-side areas inthese blocks.

When an error distribution is not uniform in this way, there is aproblem that areas in which errors which inevitably become large occuras indicated in the right sides of (a) in FIG. 26 when deblockingfiltering having a symmetrical filter characteristic is performed onblock boundaries. In other words, when an area having a large error andan area having a small error neighbor each other, an unnecessary erroris inevitably included in the pixels which originally have a smallerror.

For this reason, in this embodiment, an error distribution is estimatedbased on the basis used in the orthogonal transform of a block, anddeblocking filtering is performed based on the result. In this way, asindicated in (b) of FIG. 26 , it is possible to reduce errors in thepixels which have originally a large error without including an error inthe pixels which have originally have a small error.

FIG. 27 is a block diagram indicating main constituent elements of loopfilter 120 according to this embodiment.

Loop filter 120 includes: error distribution estimator 1201; filtercharacteristic determiner 1202; and filtering executor 1203.

Error distribution estimator 1201 estimates an error distribution basedon an error-related parameter. The error-related parameter is aparameter which affects the magnitude of an error, and, for example,indicates each of the types of bases applied in the orthogonal transformof respective two blocks across a block boundary to bedeblocking-filtered.

Filter characteristic determiner 1202 determines a filter characteristicbased on an error distribution estimated by error distribution estimator1201.

Filtering executor 1203 performs deblocking filtering with a filtercharacteristic determined by filter characteristic determiner 1202 on ablock boundary area.

FIG. 28 is a flowchart indicating schematic processing operationsperformed by loop filter 120 according to this embodiment.

First, error distribution estimator 1201 estimates an error-relatedparameter. This error-related parameter is a parameter which affects themagnitude of an error. In other words, the error-related parameter isinformation which characterizes an error distribution in an area to be atarget of deblocking filtering. Specifically, an error-related parameterindicates the types of the bases applied in the orthogonal transform oftwo blocks across a block boundary to be deblocking-filtered, that is, acombination of bases for the two blocks. Error distribution estimator1201 estimates an error distribution in the area to be a target ofdeblocking filtering based on the error-related parameter (Step S1201).Specifically, error distribution estimator 1201 selects an i(1≤i≤N)-therror distribution corresponding to the error-related parameter fromerror distributions classified into N. In this way, the errordistribution is estimated.

Next, filter characteristic determiner 1202 determines a filtercharacteristic according to the estimated distribution error (StepS1202). In other words, filter characteristic determiner 1202 refers toa table in which filter characteristics are associated one-to-one withthe N error distributions. Filter characteristic determiner 1202 thenfinds out, from the table, the filter characteristic associated with theerror distribution estimated in Step S1201. In this way, the filtercharacteristic is determined.

Lastly, filtering executor 1203 executes deblocking filtering in whichthe filter characteristic determined in Step S1202 is reflected onto animage indicated by an input signal (Step S1203). It is to be noted thatthe image indicated by the input signal is, for example, a reconstructedimage.

In this embodiment, the error-related parameter indicates the types ofthe bases used in the transform of blocks. Accordingly, in thisembodiment, deblocking filtering is performed based on the bases Forexample, loop filter 120 determines, as a filter characteristic, atleast one of filter coefficients and a threshold value according to acombination of orthogonal transform bases used for two blocks whichneighbor each other. In other words, the filter coefficient and thethreshold value are designed based on the magnitude relationship betweenerrors. Loop filter 120 then performs deblocking filtering with thedetermined filter characteristic on a current pixel.

In other words, encoder 100 according to this embodiment includes, forexample, processing circuitry and memory. The processing circuitryperforms the following processing using the memory. In other words, theprocessing circuitry transforms, using a basis, each of blocks eachincluding a plurality of pixels into a block including a plurality oftransform coefficients. Next, the processing circuitry performs at leastinverse transform on each of the blocks each including the plurality oftransform coefficients to reconstruct the block including the pluralityof pixels. Next, the processing circuitry determines a filtercharacteristic for the boundary between two blocks which neighbor eachother and have been reconstructed, based on a combination of bases usedto transform the two blocks. The processing circuitry then performsdeblocking filtering with the determined filter characteristic.

It is to be noted that, for example, the processing circuitry includes acentral processing unit (CPU), and functions as loop filter 120indicated in FIG. 1 . In addition, the memory may be block memory 118 orframe memory 122, or another memory.

Likewise, decoder 200 according to this embodiment includes, forexample, processing circuitry and memory. The processing circuitryperforms the following processing using the memory. In other words, theprocessing circuitry performs at least inverse transform on each of theblocks each including a plurality of transform coefficients obtained bytransform using a basis, to reconstruct a block including a plurality ofpixels. Next, the processing circuitry determines a filtercharacteristic for the boundary between two blocks which neighbor eachother and have been reconstructed, based on a combination of basesrespectively used to transform the two blocks. The processing circuitrythen performs deblocking filtering with the determined filtercharacteristic.

It is to be noted that, for example, the processing circuitry includes acentral processing unit (CPU), and functions as loop filter 212indicated in FIG. 10 . In addition, the memory may be block memory 210or frame memory 214, or any other memory.

In this way, the filter characteristic for the boundary between the twoblocks which neighbor each other and have been reconstructed aredetermined based on the combination of the bases used to transform therespective two blocks. Thus, for example, it is possible to determine anasymmetrical filter characteristic for the boundary. As a result, evenwhen errors vary between pixel values of pixels in the two blocks acrossthe boundary, it is possible to increase the possibility of reducingerrors by performing deblocking filtering with an asymmetrical filtercharacteristic.

FIG. 29 is a block diagram indicating specific constituent elements ofloop filter 120 according to this embodiment.

As in the configuration indicated in FIG. 27 , loop filter 120 includes:error distribution estimator 1201; filter characteristic determiner1202; and filtering executor 1203. Loop filter 120 further includes:switches 1205, 1207, and 1209; boundary determiner 1204; filterdeterminer 1206; and processing determiner 1208.

Boundary determiner 1204 determines whether a pixel to bedeblocking-filtered (that is, a current pixel) is present around a blockboundary. Boundary determiner 1204 then outputs the determination resultto switch 1205 and processing determiner 1208.

In the case where boundary determiner 1204 has determined that a pixelto be deblocking-filtered is present around a block boundary, switch1205 outputs a pre-filtering image to switch 1207. In the opposite casewhere boundary determiner 1204 has determined that no pixel to bedeblocking-filtered is present around a block boundary, switch 1205outputs a pre-filtering image to switch 1209.

Filter determiner 1206 determines whether to perform deblockingfiltering on a current pixel, based on the pixel value of at least oneneighboring pixel around the current pixel and an error distributionestimated by error distribution estimator 1201. Filter determiner 1206then outputs the determination result to switch 1207 and processingdeterminer 1208.

In the case were filter determiner 1206 has determined to performdeblocking filtering on the current pixel, switch 1207 outputs thepre-filtering image obtained through switch 1205 to filtering executor1203. In the opposite case where filter determiner 1206 has determinednot to perform deblocking filtering on the current pixel, switch 1207outputs the pre-filtering image obtained through switch 1205 to switch1209.

When obtaining the pre-filtering image through switches 1205 and 1207,filtering executor 1203 executes, on the current pixel, deblockingfiltering with the filter characteristic determined by filtercharacteristic determiner 1202. Filtering executor 1203 outputs thefiltered pixel to switch 1209.

Under control by processing determiner 1208, switch 1209 selectivelyoutputs a pixel which has not been deblocking-filtered and a pixel whichhas been deblocking-filtered by filtering executor 1203.

Processing determiner 1208 controls switch 1209 based on the results ofdeterminations made by boundary determiner 1204 and filter determiner1206. In other words, processing determiner 1208 causes switch 1209 tooutput the pixel which has been deblocking-filtered when boundarydeterminer 1204 has determined that the current pixel is present aroundthe block boundary and filter determiner 1206 has determined to performdeblocking filtering on the current pixel. In addition, other than theabove case, processing determiner 1208 causes switch 1209 to output thepixel which has not been deblocking-filtered. A filtered image is outputfrom switch 1209 by repeating output of a pixel in this way.

FIG. 30 is a diagram indicating an example of a debloking filter havinga symmetrical filtering characteristic with respect to a block boundary.

In HEVC deblocking filtering, one of two deblocking filters havingdifferent properties, that is, a strong filter and a weak filter isselected using pixel values and quantization parameters. In the case ofa strong filter, pixels p0 to p2 and pixels q0 to q2 are present acrossa block boundary as indicated in FIG. 30 , the pixel values of therespective pixel q0 to q2 are changed to pixel values q′0 to q′2 byperforming calculations according to the expressions below.q′0=(p1+2×p0+2×q0+2×q1+q2+4)/8q′1=(p0+q0+q1+q2+2)/4q′2=(p0+q0+q1+3×q2+2×q3+4)/8

It is to be noted that, in the above expressions, p0 to p2 and q0 to q2are the pixel values of respective pixels p0 to p2 and pixels q0 to q2.In addition, q3 is the pixel value of neighboring pixel q3 at theopposite side with respect to the block boundary. In addition, in theright side of each of the expressions, coefficients which are multipliedwith respective pixels to be used for deblocking filtering are filtercoefficients.

Furthermore, in the HEVC deblocking filtering, clipping is performed sothat the calculated pixel values do not change over a threshold value.In the clipping, the pixel values calculated according to the aboveexpressions are clipped to a value obtained according to “apre-calculation pixel value ±2×a threshold value” using the thresholdvalue determined based on a quantization parameter. In this way, it ispossible to prevent excessive smoothing.

However, in such deblocking filtering, change in pixel value isdetermined based on the pixel value of a neighboring pixel and aquantization parameter, and a filter characteristic is designed withoutreflecting non-uniformity in error distribution in a block. Accordingly,a problem as indicated in (a) of FIG. 26 may occur.

In view of this, loop filter 120 according to this embodiment determinesa filter characteristic in deblocking filtering by reflectingnon-uniformity in error distribution in a block. Specifically, errordistribution estimator 1201 estimates that the pixel value of a pixellocated at a position at which the amplitude of a basis is largerincludes a larger error. Next, filter characteristic determiner 1202determines a filter characteristic based on an error distributionestimated by error distribution estimator 1201. Here, when determiningfilter coefficients included in a filter characteristic, filtercharacteristic determiner 1202 determines a smaller filter coefficientfor a pixel having a large error so that a pixel having a small error isless affected by the neighboring pixel having the large error. Inaddition, filter characteristic determiner 1202 determines a largefilter coefficient for the pixel having the small error so that thepixel having the large error is more affected by the neighboring pixelhaving the small error.

In other words, the filter coefficients or the threshold valuedetermined by loop filter 120 do(es) not always to be symmetrical withrespect to a block boundary. Loop filter 120 determines a large filtercoefficient for a pixel having a small error when performing deblockingfiltering on a current pixel having a large error. In addition, loopfilter 120 determines a small filter coefficient for a pixel having alarge error when performing deblocking filtering on a current pixelhaving a small error, among two pixels across a block boundary.

In other words, in the determination of a filtering characteristic inthis embodiment, the processing circuitry determines a smaller filtercoefficient for a pixel present at a position at which the amplitude ofa basis used to transform the block is larger. In addition, as describedabove, a transform coefficient for a lower-order basis is likely to belarger than a transform coefficient for a higher-order basis.Accordingly, the amplitude of the basis is, for example, the amplitudeof a low-order basis, and is the amplitude of a zero-order basis.

For example, a pixel located at a position at which the amplitude of abasis is larger is likely to have a pixel value with a larger error.Encoder 100 according to this embodiment determines a small filtercoefficient for the pixel whose pixel value has the large error.Accordingly, deblocking filtering with such filter coefficients furtherreduces influence of the pixel value with the large error onto the pixelvalue with the small error. In short, the deblocking filtering furtherincreases the possibility of error reduction. In addition, a lower-orderbasis affects errors more significantly. Accordingly, it is possible tofurther increase the possibility of error reduction by determining asmall filter coefficient for a pixel located at a position at which theamplitude of a zero-order basis is larger.

It is to be noted that error distribution estimator 1201 may use, as anerror-related parameter, at least one of an orthogonal transform basis,a block size, the presence or absence of a pre-stage filter, an intraprediction direction, the number of reference pictures in interprediction, a quantization parameter, etc.

FIGS. 31 to 35 are each a diagram indicating an example of an orthogonaltransform basis for each block size. In other words, these diagramsindicate examples of the orthogonal transform bases in the cases wherethe block sizes are respectively N=31, 16, 8, and 4. Specifically, FIG.31 indicates zero-order to fifth-order bases in DCT-II, FIG. 32indicates zero-order to fifth-order bases in DCT-V, and FIG. 33indicates zero-order to fifth-order bases in DCT-VIII. FIG. 34 indicateszero-order to fifth-order bases in DST-I, and FIG. 35 indicateszero-order to fifth-order bases in DST-VII. It is to be noted that thehorizontal axis of the graph in each of FIGS. 31 to 35 indicatespositions on a one-dimensional space, and the vertical axis thereofindicates basis values (that is, amplitudes).

Error distribution estimator 1201 estimates error distributions based onbases such as DCT-II, DCT-V, DCT-VIII, DST-I, and DST-VII indicated inFIGS. 31 to 35 . At this time, error distribution estimator 1201 mayfurther estimate the error distributions based on the block sizes of theblocks to which orthogonal transform using these bases have beenapplied, that is, the number of pixels N.

<Specific Example of DST-VII/DST-VII>

FIG. 36 is a diagram indicating examples of filter coefficients to bedetermined.

For example, as indicated in FIG. 36 , loop filter 120 performsdeblocking filtering on current pixel p0. It is to be noted that, forexample, block P and block Q neighbor in the horizontal direction, andcurrent pixel p0 is present at a position in block P close to a boundary(that is, a block boundary) with block Q.

Here, for example, each of block P and block Q is a blockorthogonal-transformed using DST-VII. In such a case, as indicated inFIG. 35 , the amplitude of a low-order basis (specifically, a zero-orderbasis) is small in the upper-side and left-side areas in blocks, and theamplitude of a low-order basis is large in the lower-side and right-sideareas in blocks.

Accordingly, when block P and block Q neighbor in the horizontaldirection, the amplitude of a low-order basis (specifically, azero-order basis) is large in left-side block P around the blockboundary, that is, the right side in block P. In addition, the amplitudeof a low-order basis is small in right-side block Q around the blockboundary, that is, the left-side in block Q.

As a result, error distribution estimator 1201 estimates a large errorin an area of block P around the block boundary, and estimates a smallerror in an area of block Q around the block boundary. In this way, anerror distribution around the block boundary is estimated.

Filter characteristic determiner 1202 determines, as a filtercharacteristic, a filter coefficient of, for example, a 5-tap deblockingfilter, based on the estimated error distribution.

It is to be noted that the 5-tap deblocking filter is a deblockingfilter using five pixels arranged in the horizontal direction. Whenpixel p0 is a current pixel, the five pixels are pixels p2, p1, p0, q0,and q1. In addition, the filter coefficient of the 5-tap deblockingfilter which becomes a reference is, for example, (1, 2, 2, 2, 1)/8. Byperforming a calculation using the reference filter coefficient, thatis, according to p′0=(1×p2+2×p1+2×p0+2×q0+1×q1)/8, calculated pixelvalue p′0 of current pixel p0 is obtained.

When the above-described error distribution has been estimated, filtercharacteristic determiner 1202 according to this embodiment determines afilter coefficient different from the above reference as a filtercharacteristic. Specifically, filter characteristic determiner 1202determines a small filter coefficient for a pixel at a position at whichan error has been estimated to be large in block P, and determines alarge filter coefficient for a pixel at a position at which an error hasbeen estimated to be small in block Q. More specifically, as indicatedin FIG. 36 , filter characteristic determiner 1202 determines filtercoefficients 0.5, 1.0, 1.0, 2.0, and 1.5 as in (0.5, 1.0, 1.0, 2.0,1.5)/6 respectively for pixels p2, p1, p0, q0, and q1, for performingdeblocking filtering on current pixel p0 in block P. In this case, afilter coefficient which is determined for pixel p0 at the position atwhich an error has been estimated to be large in block P is “1.0/6”, anda filter coefficient which is determined for pixel q0 at the position atwhich an error has been estimated to be small in block P is “2.0/6”. Inother words, the filter coefficient for pixel p0 is smaller than thefilter coefficient for pixel q0, and the filter coefficient for pixel q0is larger than the filter coefficient for pixel p0.

As a result, by performing the calculation using the filter coefficientdetermined in this way, that is, according top′0=0.5×p2+1.0×p1+1.0×p0+2.0×q0+1.5×q1)/6, calculated pixel value p′0 ofcurrent pixel p′0 is obtained. The calculated pixel value p′0 is adeblocking-filtered pixel value of current pixel p0.

Here, filter characteristic determiner 1202 according to this embodimentmay determine a threshold value for clipping as a filter characteristic,based on the estimated error distribution. It is to be noted that thethreshold value is the above-described reference value or clip width.For example, filter characteristic determiner 1202 determines a largethreshold value for a pixel at a position at which the amplitude of abasis has been estimated to be large, that is, an error has beenestimated to be large. In contrast, filter characteristic determiner1202 determines a small threshold value for a pixel at a position atwhich the amplitude of a basis has been estimated to be small, that is,an error has been estimated to be small. It is to be noted that theamplitude of the basis is, for example, the amplitude of a low-orderbasis, that is for example, the amplitude of a zero-order basis. Forexample, when a reference threshold value is 10, filter characteristicdeterminer 1202 determines, to be 12, a threshold value for a right-sidepixel in block P with respect to and close to a block boundary, anddetermines, to be 8, a threshold value for a left-side pixel in block Qwith respect to and close to the block boundary.

When a threshold value is determined for current pixel p0, filteringexecutor 1203 performs clipping on pixel value p′0 calculated fromcurrent pixel p0. The threshold value determined for current pixel p0is, for example, 12. In view of this, when the amount of change frompixel value p0 before the calculation to calculated pixel value p′0 islarger than a threshold value of 12, filtering executor 1203 clipscalculated pixel value p′0 to either a pixel value (p0+12) or a pixelvalue (p0−12). More specifically, filtering executor 1203 clipscalculated pixel value p′0 to (p0−12) when (p0−p′0)>12 is satisfied, andclips calculated pixel value p′0 to (p0+12) when (p0−p′0)<−12 issatisfied. In this way, either the pixel value (p0+12) or the pixelvalue (p0−12) is determined to be a deblocking-filtered pixel value p′0of current pixel p0. In contrast, when the amount of change is smallerthan or equal to 12, the calculated pixel value p′0 is determined to bea deblocking-filtered pixel value of current pixel p0.

In this way, in this embodiment, the two blocks include the first blockand the second block located at the right side of or below the firstblock. When determining the filter characteristic, when the basis usedto transform a first block is a first basis and the basis used totransform a second block is a second basis, the processing circuitrydetermines, as the filter characteristic, each of a first filtercoefficient for a pixel around the boundary in the first block and asecond filter coefficient for a pixel around the boundary in the secondblock, based on the first basis and the second basis. More specifically,when the first basis and the second basis are of DST-VII (DST denotesdiscrete sine transforms), the processing circuitry determines, as thefilter characteristic, the second filter coefficient which is largerthan the first filter coefficient.

In the case where the first basis and the second basis are of DST-VII,it is highly likely that an error in a first block around a boundary islarge and an error in a second block around the boundary is small.Accordingly, it is possible to further increase the possibility ofreducing errors appropriately around the boundary by determining asecond filter coefficient which is larger than a first filtercoefficient in such a case and performing deblocking filtering with thefirst and second filter coefficients.

In addition, based on a combination of bases for the first block and thesecond block, the processing circuitry further determines, as the filtercharacteristic, each of the first threshold value for the first blockand the second threshold value for the second block. The processingcircuitry then performs a calculation on the pixel value of a currentpixel using a first filter coefficient and a second filter coefficientto obtain a calculated pixel value of the current pixel. Next, theprocessing circuitry determines whether the amount of change from thepre-calculation pixel value of each target pixel to the calculated pixelvalue is larger than the threshold value for the block to which thecurrent pixel belongs among a first threshold value and a secondthreshold value. When the amount of change is larger than the thresholdvalue, the processing circuitry then clips the calculated pixel value ofthe current pixel to the sum of or difference between thepre-calculation pixel value of the current pixel and the thresholdvalue.

In this way, when the amount of change in calculated pixel value of thecurrent pixel is larger than the threshold value, the calculated pixelvalue of the current pixel is clipped to the sum of or differencebetween the pre-calculation pixel value of the current pixel and thethreshold value. Thus, it is possible to prevent the target pixel valueof the current pixel from being changed significantly by the deblockingfiltering. In addition, the first threshold value for the first blockand the second threshold value for the second block are determined basedon the combination of bases for the first block and the second block.Accordingly, for each of the first block and the second block, it ispossible to determine a large threshold value for a pixel located at aposition at which the amplitude of a basis is large, that is, a pixelhaving a large error, and determine a small threshold value for a pixellocated at a position at which the amplitude of a basis is small, thatis a pixel having a small error. As a result, the deblocking filteringmakes it possible to allow the pixel value of the pixel having the largeerror to change significantly and prohibit the pixel value of the pixelhaving the small error from changing significantly. Accordingly, it ispossible to further increase the possibility of reducing errorsappropriately around the boundary between the first block and the secondblock.

<Specific Example of DST-VII/DCT-II>

FIG. 37 is a diagram indicating other examples of filter coefficients tobe determined.

For example, as indicated in FIG. 37 similarly in the example indicatedin FIG. 36 , loop filter 120 performs deblocking filtering on currentpixel p0.

Here, for example, block P is a block orthogonal-transformed usingDST-VII, and block Q is a block orthogonal-transformed using DCT-II. Insuch a case, as indicated in FIG. 35 , the amplitude of a low-orderbasis (specifically, a zero-order basis) is small in the upper-side andlower-side areas in block P, and the amplitude of a low-order basis islarge in the lower-side and right-side areas in block P. In comparison,as indicated in FIG. 31 , in block Q, the amplitude of a low-order basisis constant, but is larger than the amplitude in the upper-side and theleft-side areas of block P and is smaller than the amplitude in thelower-side and the right-side of block P. In other words, in block Q,the amplitude of the low-order basis is constant at a medium level.

Accordingly, when block P and block Q neighbor in the horizontaldirection, the amplitude of a low-order basis (specifically, azero-order basis) is large in right-side block P around the blockboundary, that is, the right side in block P. In addition, the amplitudeof a low-order basis is at a medium level in right-side block Q aroundthe block boundary, that is, the left side in block Q.

As a result, error distribution estimator 1201 estimates a large errorin a block boundary area in block P, and estimates a medium-level errorin a block boundary area in block Q. In this way, an error distributionaround the block boundary is estimated. In other words, an errordistribution indicating a gentler error change in the direction verticalto the block boundary than the example indicated in FIG. 36 isestimated.

Filter characteristic determiner 1202 determines, as a filtercharacteristic, a filter coefficient of, for example, a 5-tap deblockingfilter, based on the estimated error distribution. In other words,filter characteristic determiner 1202 determines a filter coefficient sothat current pixel p0 located at a position at which an error is largein block P is more affected by a pixel having a medium-level error inblock Q. In addition, since the error distribution around the blockboundary indicates the gentler error change in the direction vertical tothe block boundary, filter characteristic determiner 1202 determinesfive filter coefficients which have smaller differences with each otherthan in the example indicated in FIG. 36 . Specifically, filtercharacteristic determiner 1202 determines the filter coefficients 0.5,1.0, 1.5, 1.75, 1.25 as in (0.5, 1.0, 1.5, 1.75, 1.25)/6 for pixels p2,p1, p0, q0, q1, for performing deblocking filtering on current pixel p0in block P. In this case, a filter coefficient which is determined forpixel p0 at the position at which an error has been estimated to belarge in block P is “1.5/6”, and a filter coefficient which isdetermined for pixel q0 at the position at which an error has beenestimated to be at a medium level in block Q is “1.75/6”. In otherwords, the filter coefficient for pixel p0 is smaller than the filtercoefficient for pixel q0, and the filter coefficient for pixel q0 islarger than the filter coefficient for pixel p0. In addition, thedifference between the filter coefficient of pixel p0 and the filtercoefficient of pixel q0 is smaller than the case indicated in FIG. 36 .

In addition, even when block P and block Q neighbor in the verticaldirection, error distribution estimator 1201 estimates an errordistribution in the same manner as described above, and filtercharacteristic determiner 1202 determines a filter coefficient based onthe error distribution. Furthermore, filter characteristic determiner1202 may determine a threshold value for clipping in the same manner asin the example indicated in FIG. 36 , and filtering executor 1203 mayperform clipping using the threshold value.

<Specific Example of DST-I/DST-I>

FIG. 38 is a diagram indicating other examples of filter coefficients tobe determined.

For example, as indicated in FIG. 38 similarly in the examples indicatedin FIGS. 36 and 37 , loop filter 120 performs deblocking filtering oncurrent pixel p0.

Here, for example, each of block P and block Q is a blockorthogonal-transformed using DST-I. In such a case, as indicated in FIG.34 , the amplitude of a low-order (specifically, zero-order) basis inthe upper-side and left-side areas of a block and the amplitude of alow-order basis in the lower-side and right-side areas of the block areequal to each other.

Accordingly, when block P and block Q neighbor in the horizontaldirection, the amplitude of a low-order basis around a block boundary inblock P and the amplitude of a low-order basis around the block boundaryin block Q are equal to each other.

As a result, error distribution estimator 1201 estimates a symmetricalerror distribution for the block boundary as the error distributionaround the block boundary between block P and block Q.

In such a case, filter characteristic determiner 1202 determines thereference filter characteristic as described above, that is, asymmetrical filter characteristic for a block boundary as the filtercharacteristic based on the error distribution.

In addition, even when each of block P and block Q is a blockorthogonal-transformed using DCT-II, as described above, the amplitudeof a low-order basis around a block boundary in block P and theamplitude of a basis around a block boundary in block Q are equal toeach to other. Accordingly, even in such a case, error distributionestimator 1201 estimates a symmetrical error distribution for the blockboundary as the error distribution around the block boundary betweenblock P and block Q. In such a case, filter characteristic determiner1202 determines the reference filter characteristic as described above,that is, a symmetrical filter characteristic for a block boundary as thefilter characteristic based on the error distribution. The filtercoefficient of the 5-tap deblocking filter which becomes a reference is,for example, (1, 2, 2, 2, 1)/8. In this case, the filter coefficientwhich is determined for pixel p0 in block P is “2/8”, and the filtercoefficient which is determined for pixel q0 in block Q is “2/8”. Inother words, these filter coefficients are symmetrical with respect tothe block boundary.

In such a case, in this embodiment, when the first basis and the secondbasis are of DCT-II (DCT denotes discrete cosine transforms), the secondfilter coefficient which is equal to the first filter coefficient isdetermined as the filter coefficient.

In the case where the first basis and the second basis are of DCT-II, itis highly likely that an error in the first block around the boundaryand an error in the second block around the boundary are equal to eachother. Accordingly, it is possible to further increase the possibilityof reducing errors appropriately around the boundary by determining asecond filter coefficient which is equal to a first filter coefficientin such a case and performing deblocking filtering with the first andsecond filter coefficients.

<Specific Examples of Block Sizes>

FIG. 39 is a diagram for explaining relationships between block sizesand errors. It is to be noted that a block size is a block width or thenumber of pixels in a block. Specifically, (a) in FIG. 39 indicateszero- to fifth-order bases in DST-VII in the case of a block having ablock size of N=32, and (b) in FIG. 39 indicates zero- to fifth-orderbases in DST-VII in the case of a block having a block size of N=4. Itis to be noted that the horizontal axis of each graph in FIG. 39indicates positions on a one-dimensional space, and the vertical axisthereof indicates basis values (that is, amplitudes).

The amplitude of a basis at the block boundary varies according to ablock size which is the number of pixels of a block to beorthogonal-transformed. In view of this, error distribution estimator1201 according to this embodiment estimates an error distribution basedon the block size. In this way, it is possible to increase the accuracyof filter coefficients to be determined.

For example, as indicated in FIG. 39 , even in the case of blocksorthogonal-transformed using DST-VII, the amplitudes of bases around ablock boundary in a block having a block size of N=4 and the amplitudesof bases around a block boundary in a block having a block size of N=32vary. Specifically, in the case of the block having the block size ofN=32, as indicated in (a) of FIG. 39 , the amplitudes of zero- tofifth-order bases at position n=32 in DST-VII are all 1. It is to benoted that the position n=32 is at the right-side or lower-side end ofthe block. In the other case of the block having the block size of N=4,as indicated in (b) of FIG. 39 , some of the amplitudes of zero- tothird-order bases at position n=4 in DST-VII is smaller than 1. It is tobe noted that the position n=4 is at the right-side or lower-side end ofthe block.

Accordingly, error distribution estimator 1201 according to thisembodiment estimates small errors in the case of the block having theblock size of N=4 and estimates errors larger than the small errors inthe case of the block having the block size of N=32, as the errors inthe right side and lower side of the blocks orthogonal-transformed usingDST-VII.

FIG. 40 is a diagram indicating still other examples of filtercoefficients to be determined.

For example, as indicated in FIG. 40 similarly in the examples indicatedin FIGS. 36 to 38 , loop filter 120 performs filtering on current pixelp0.

Here, for example, block P is a block having a block size of N=32orthogonal-transformed using DST-VII, and block Q is a block having ablock size of N=4 orthogonal-transformed using DST-VII. In such a case,as indicated in (a) of FIG. 39 , the amplitudes of a low-order(specifically, a zero-order) basis are small in the upper-side andleft-side areas in block P, and the amplitudes of a low-order basis arelarge in the lower-side and right-side areas in block P. On thecontrary, as indicated in (b) of FIG. 39 , the amplitudes of low-orderbasis in the upper-side and left-side areas of block Q are at a mediumlevel.

As a result, error distribution estimator 1201 estimates a large errorin the block boundary area of block P, and estimates a medium-levelerror in the block boundary area of block Q. In this way, an errordistribution around the block boundary is estimated. In other words, anerror distribution indicating a gentler error change in the directionvertical to the block boundary than the example indicated in FIG. 36 .

Filter characteristic determiner 1202 determines, as a filtercharacteristic, a filter coefficient of, for example, a 5-tap deblockingfilter, based on the estimated error distribution. In other words,filter characteristic determiner 1202 determines the filter coefficientso that current pixel p0 located at a position at which an error islarge in block P is more affected by a pixel having a medium-level errorin block Q. In addition, since the error distribution around the blockboundary indicates the gentler error change in the direction vertical tothe block boundary, filter characteristic determiner 1202 determinesfive filter coefficients which have smaller differences with each otherthan in the example indicated in FIG. 36 . Specifically, filtercharacteristic determiner 1202 determines the filter coefficients 0.5,1.0, 1.5, 1.75, 1.25 as in (0.5, 1.0, 1.5, 1.75, 1.25)/6 for pixels p2,p1, p0, q0, q1, for performing deblocking filtering on current pixel p0in block P. In this case, a filter coefficient which is determined forpixel p0 at the position at which an error has been estimated to belarge in block P is “1.5/6”, and a filter coefficient which isdetermined for pixel q0 at the position at which an error has beenestimated to be at a medium level in block Q is “1.75/6”. In otherwords, the filter coefficient for pixel p0 is smaller than the filtercoefficient for pixel q0, and the filter coefficient for pixel q0 islarger than the filter coefficient for pixel p0. In addition, thedifference between the filter coefficient of pixel p0 and the filtercoefficient of pixel q0 is smaller than the example indicated in FIG. 36.

In this way, in this embodiment, in the case where the first basis andthe second basis are of DST-VII (DST denotes discrete sine transforms)and the size of the second block is smaller than the size of the firstblock, when determining the filtering characteristic, the processingcircuitry may determine, as the filter characteristic, the second filtercoefficient which is larger than the first filter coefficient. Here, thedetermined filter coefficient gradient between the first filtercoefficient and the second filter coefficient is gentler than in thecase where the first block and the second block are equal in size.

In the case where the first basis and the second basis are of DST-VIIand the size of the second block is smaller than the size of the firstblock, it is likely that an error in the first block around the boundaryis large and an error in the second block around the boundary is at amedium level. In other words, it is likely that an error distributionbetween the first block and the second block around the boundary has agentle gradient.

Encoder 100 according to this embodiment determines the second filtercoefficient which is larger than the first filter coefficient in such acase, and performs deblocking filtering with the first and second filtercoefficients. Here, the determined filter coefficient gradient betweenthe first filter coefficient and the second filter coefficient isgentler than in the case where the first block and the second block areequal in size. Accordingly, even when the error distribution around theboundary between the first block and the second block has a gentlegradient, it is possible to increase the possibility of reducing errorsappropriately around the boundary.

Variation 1

Filtering executor 1203 performs deblocking filtering also on a pixelhaving a small error in Embodiment 7, but deblocking filtering may beOFF for a pixel having a small error. It is to be noted that switchingOFF deblocking filtering is equivalent to setting a filter coefficientfor a current pixel to 1 and setting a filter coefficient for pixelsother than the current pixel to 0.

In addition, in Embodiment 7, filter determiner 1206 and filtercharacteristic determiner 1202 perform processing based on the errordistribution estimated by error distribution estimator 1201. However,filter determiner 1206 may determine whether to perform filtering usingonly a quantization parameter, and filter characteristic determiner 1202may determine a filter characteristic based on the quantizationparameter and an orthogonal transform basis.

In addition, in this variation, deblocking filtering may be performed oneach of a luminance signal and a chrominance signal. In this case, loopfilter 120 may design a deblocking filter for the luminance signal and adeblocking filter for the chrominance signal independently of ordependently on each other. For example, loop filter 120 may performdeblocking filtering according to Embodiment 7 only on one signal amongthe luminance signal and the chrominance signal, and may perform otherdeblocking filtering on the other signal.

In addition, in this variation, for example, loop filter 120 may performdeblocking filtering according to Embodiment 7 only on an intraprediction block. Alternatively, loop filter 120 may perform deblockingfiltering according to Embodiment 7 on both an intra prediction blockand an inter prediction block.

In addition, loop filter 120 may switch between ON and OFF of deblockingfiltering according to Embodiment 7, in units of a slice, a tile, awavefront dividing unit, or a CTU.

In addition, there is also a technique for increasing coefficientdeviation in frequency space and increasing a compression efficiency byfurther performing transform after orthogonal transform (for example,Non-Separable Secondary Transform in JVET). Also at this time, loopfilter 120 may determine a filter characteristic based on an orthogonaltransform basis.

In addition, for example, there is a case where orthogonal transformusing DST-VII is performed on a first block in each of first and secondtransform, and orthogonal transform using DST-VII is performed on asecond block in a first transform and orthogonal transform using DCT-IIis performed on the second block in a second transform. In such a case,loop filter 120 estimates a sharper error distribution for the firstblock than for the second block. In other words, the error distributiongradient in the horizontal direction and the vertical direction of thefirst block is sharper than the error distribution gradient of thesecond block. Loop filter 120 then determines a filter characteristicbased on the sharp error distribution.

In addition, a first transform and a second transform may be performedon blocks having different block sizes. In such a case, loop filter 120performs deblocking filtering on at least one of the two blocks havingdifferent block sizes.

In addition, when deblocking filtering according to Embodiment 7 isperformed on inter prediction blocks, it is predicted that coefficientdistributions or absolute values in respective frequencies afterorthogonal transforms vary according to prediction methods. Theseprediction methods include, for example, Uni-pred (prediction using onereference picture) and Bi-pred (prediction using two referencepictures).

Accordingly, loop filter 120 may determine a filter coefficientaccording to a prediction method. For example, loop filter 120 decreasesa weight for a filter on a Uni-pred block which tends to have acoefficient whose absolute value is large to be smaller than a weightfor a Bi-pred block.

In addition, loop filter 120 may independently determine a filter weightfor a block to which the merge mode has been applied. For example, loopfilter 120 increases or decreases a filter weight for block to whichmerge mode has been applied to be larger than a filter weight for ablock to which prediction other than the merge mode has been applied.

In addition, deblocking filtering according to Embodiment 7 not onlymakes an image to be processed closer to an original image, but alsomakes block boundaries less noticeable similarly to conventionaldeblocking filtering. For this reason, if not only objective evaluationbut also subjective evaluation are considered to be important, it iseffective to change a filter characteristic for each block size.

More specifically, since block noise is noticeable in a block having alarge error, loop filter 120 may set filter coefficients at both sidesacross a block boundary, a threshold value, or the number of filter tapsto be larger than those for a block having a small error.

Specifically, since a correlation between pixels is higher as thedistance between pixels is shorter, it is considered that objectiveevaluation deteriorates as a pixel more distant from a current pixel isused for deblocking filtering on the current pixel. However, block noisebecomes subjectively less noticeable as a larger number of pixels areused for deblocking filtering. Accordingly, based on a trade-off betweenan objective evaluation and a subjective evaluation, loop filter 120 mayuse even a pixel distant from a current pixel in deblocking filtering onthe current pixel.

In addition, in Embodiment 7, an error distribution is estimatedaccording to bases such as DCT and DST, and a filter characteristic isdetermined based on the estimated error distribution. However, a filtercharacteristic may be determined by estimating an error distributionaccording to another transform approach instead of these bases, and afilter characteristic may be determined based on the estimated errordistribution. Examples of the other transform approach includeKarhunen-Loeve Transform (KLT), Discrete Fourier transform (DFT),Wavelet transform, and lapped transform.

In addition, encoder 100 according to Embodiment 7 includes errordistribution estimator 1201 and estimates an error distribution, butdoes not need to include error distribution estimator 1201. In otherwords, encoder 100 may directly determine a filter characteristic basedon a basis used to transform a block without estimating an errordistribution.

Variation 2

In Embodiment 7 and Variation 1 thereof, deblocking filtering with afilter characteristic determined based on a combination of bases hasbeen performed, but loop filtering other than the deblocking filteringmay be performed.

For example, loop filter 120 may determine a SAO (Sample AdaptiveOffset) filter coefficient using a basis used for transform and theposition of a current pixel in a block. Alternatively, loop filter 120may perform tri-lateral filtering based on three parameters. These threeparameters include, for example, the difference between pixel values,the distance between pixels, and an error distribution which isestimated based on orthogonal transform bases. Alternatively, loopfilter 120 may perform, in an intra processing loop, filtering accordingto Embodiment 7 or filtering in which deblocking filtering according toVariation 1 is applied. In addition, loop filter 120 does not need tochange the pixel value of a current pixel based on information about aneighboring pixel, and may give, for each current pixel, an offsetaccording to an error distribution.

In addition, loop filter 120 does not need to obtain an error-relatedparameter for each filtering if loop filter 120 can predict an errordistribution. For example, in an intra prediction block by JointExploration Model (JEM) 4.0 software, errors are unlikely to be includedin the upper side and the left side of a block, and errors are likely tobe included in the lower side and the right side of the block, becauseof the design of EMT as described above. Accordingly, considering thisin advance, loop filter 120 may perform deblocking filtering with a weakfilter strength in the upper side and the left side of a JEM 4.0 intraprediction block.

Although filter determiner 1206 determines whether to perform deblockingfiltering on a current pixel in Embodiment 7 or Variation 1 thereof,deblocking filtering may be performed on all block boundaries withoutmaking such a determination.

In addition, in Embodiment 7 or Variation 1 thereof, loop filter 120performs deblocking filtering with a filter characteristic determinedbased on a combination of bases, on a block boundary betweenreconstructed blocks to be output from adder 116. Here, for example,encoder 100 may include a filter different from loop filter 120. Inother words, the different filter performs filtering on thereconstructed blocks, and loop filter 120 performs deblocking filteringon the block boundary between reconstructed blocks filtered by thedifferent filter. In such a case, loop filter 120 may determine a filtercharacteristic in deblocking filtering, based also on a filtercharacteristic of the different filter, together with a combination ofbases. Furthermore, the different filter may perform deblockingfiltering with a symmetrical filter characteristic with respect to theblock boundary. In this case, the filter coefficients used by thedifferent filter may be set to be smaller than filter coefficients inthe case where loop filter 120 according to Embodiment 7 or Variation 1thereof is not included in encoder 100. In addition, the differentfilter may perform bilateral filtering based on two parameters asdeblocking filtering with a symmetrical filter characteristic withrespect to a block boundary. These two parameters include, for example,the difference between pixel values and the distance between pixels. Inthis case, loop filter 120 may determine filter coefficients smaller onthe whole than filter coefficients indicated in FIGS. 36 to 38, and 40 .

In addition, although loop filter 120 performs deblocking filtering on ablock boundary in Embodiment 7 or Variation 1 thereof, loop filter 120may perform filtering on a block area which is not a block boundaryarea. For example, loop filter 120 may change the pixel value of a pixelhaving a large error using the pixel value of a pixel having a smallerror in a block. Hereinafter, such filtering is referred to as in-blockfiltering.

Specifically, as indicated in FIG. 35 , in a blockorthogonal-transformed using DST-VII, the error of a pixel located atthe upper side or the left side of the block is small, and the error ofa pixel located at the lower side or the right side of the block islarge. Accordingly, loop filter 120 changes the pixel value of the pixellocated at the lower side or the right side using the pixel value of thepixel located at the upper side or the left side by performing in-blockfiltering. In this way, it is possible to increase the possibility thaterrors are reduced.

FIG. 41 is a diagram indicating basis gradients that vary depending onblock sizes. It is to be noted that the horizontal axis of each graph inFIG. 41 indicates positions on a one-dimensional space, and the verticalaxis thereof indicates basis values (that is, amplitudes).

As indicated in (a) of FIG. 41 , the amplitude of a zero-order basis inDST-VII in the case of a block having a block size of N=32 increases toabout ten times from position n=1 to position n=32 in theone-dimensional space. On the contrary, the amplitude of a zero-orderbasis in DST-VII in the case of a block having a block size of N=4increases to about three times from position n=1 to position n=4 in theone-dimensional space.

Accordingly, when the block sizes are different, a basis gradient in alarger block is gentler than a basis gradient in a smaller block evenwhen the same basis is used to transform the respective two blocks.

In other words, as described above, when loop filter 120 performsin-block filtering, it is possible to provide a greater effect ofincreasing the possibility of error reduction in a block in which alow-order basis gradient in orthogonal transform is sharp, that is, in asmaller block.

In addition, even in the case of a block having a large block size, whenthe correlation between pixels in the block have a weak distancedependency or a weak direction dependency, it is possible to increasethe possibility of error reduction by means of loop filter 120performing in-block filtering. For example, an intra predictiondirection affects a distance dependency or a direction dependency of thecorrelation between pixels. The distance dependency is a property thatthe correlation between the pixel values of pixels is higher when thedistance between the two pixels is shorter. The direction dependency isa property that the correlation between the pixel values of pixelsaccording to the direction from one of the pixels to the other pixel andthe correlation between the pixel values of the pixels according to theopposite direction vary. In view of this, loop filter 120 may change thepixel value of a pixel having a large error by performing in-blockfiltering according to an intra prediction direction.

[Mouting Example]

FIG. 42 is a block diagram indicating a mounting example of encoder 100according to each of the embodiments. Encoder 100 includes processingcircuitry 160 and memory 162. For example, a plurality of constituentelements of encoder 100 indicated in FIG. 1 are mounted on processingcircuitry 160 and memory 162 indicated in FIG. 42 .

Processing circuitry 160 is circuitry for performing informationprocessing and accessible to memory 162. For example, processingcircuitry 160 is an exclusive or general electronic circuit for encodingvideo. Processing circuitry 160 may be a processor such as a CPU.Alternatively, processing circuitry 160 may be an assembly of aplurality of electronic circuits. In addition, for example, processingcircuitry 160 may take the roles of two or more of the constituentelements other than the constituent elements for storing informationamong the plurality of constituent elements of encoder 100 indicated inFIG. 1 .

Memory 162 is exclusive memory or general memory in which informationused by processing circuitry 160 to encode video is stored. Memory 162may be an electronic circuit, or may be connected to processingcircuitry 160. In addition, memory 162 may be included in processingcircuitry 160. Alternatively, memory 162 may be an assembly of aplurality of electronic circuits. In addition, memory 162 may be amagnetic disc, an optical disc, or the like, or may be represented asstorage, a recording medium, or the like. In addition, memory 162 may benon-volatile memory, or volatile memory.

For example, in memory 162, video to be encoded may be stored or abitstream corresponding to encoded image information may be stored. Inaddition, a program that is executed by processing circuitry 160 toencode video may be stored in memory 162.

In addition, for example, memory 162 may take the roles of two or moreof the constituent elements other than the constituent elements forstoring information among the plurality of constituent elements ofencoder 100 indicated in FIG. 1 . More specifically, memory 162 may takethe roles of block memory 118 and frame memory 122 indicated in FIG. 1 .More specifically, processed sub-blocks, processed blocks, and processedpictures, etc. may be stored in memory 162.

It is to be noted that, in encoder 100, not all the plurality ofconstituent elements indicated in FIG. 1 , etc. may be mounted, or notall the plurality of processes described above may be performed. Part ofthe plurality of constituent elements indicated in FIG. 1 , etc. may beincluded in one or more other devices, and part of the plurality ofprocesses described above may be performed by the one or more otherdevices. In encoder 100, part of the plurality of constituent elementsindicated in FIG. 1 , etc. may be mounted, and a video can beefficiently processed with a small coding amount by means of part of theabove-described processes being executed.

FIG. 43 is a block diagram indicating a mounting example of decoder 200according to each of the embodiments. Decoder 200 includes processingcircuitry 260 and memory 262. For example, a plurality of constituentelements of decoder 200 indicated in FIG. 10 are mounted as processingcircuitry 260 and memory 262 indicated in FIG. 43 .

Processing circuitry 260 is circuitry for performing informationprocessing and accessible to memory 262. For example, processingcircuitry 260 is an exclusive or general electronic circuit for decodingvideo. Processing circuitry 260 may be a processor such as a CPU.Alternatively, processing circuitry 260 may be an assembly of aplurality of electronic circuits. In addition, for example, processingcircuitry 260 may take the roles of two or more of the constituentelements other than the constituent elements for storing informationamong the plurality of constituent elements of decoder 200 indicated inFIG. 10 .

Memory 262 is exclusive memory or general memory in which informationused by processing circuitry 260 to decode video is stored. Memory 262may be an electronic circuit, or may be connected to processingcircuitry 260. In addition, memory 262 may be included in processingcircuitry 260. Alternatively, memory 262 may be an assembly of aplurality of electronic circuits. In addition, memory 262 may be amagnetic disc, an optical disc, or the like, or may be represented asstorage, a recording medium, or the like. In addition, memory 262 may benon-volatile memory, or volatile memory.

For example, in memory 262, a bitstream corresponding to an encodedvideo may be stored or a video corresponding to a decoded bitstream maybe stored. In addition, a program that is executed by processingcircuitry 260 to decode a video may be stored in memory 262.

In addition, for example, memory 262 may take the roles of two or moreof the constituent elements other than the constituent elements forstoring information among the plurality of constituent elements ofdecoder 200 indicated in FIG. 10 . More specifically, memory 262 maytake the roles of block memory 210 and frame memory 214 indicated inFIG. 10 . More specifically, processed sub-blocks, processed blocks, andprocessed pictures, etc. may be stored in memory 262.

It is to be noted that, in decoder 200, not all the plurality ofconstituent elements indicated in FIG. 10 , etc. may be mounted, or notall the plurality of processes described above may be performed. Part ofthe plurality of constituent elements indicated in FIG. 10 , etc. may beincluded in one or more other devices, and part of the plurality ofprocesses described above may be performed by the one or more otherdevices. In decoder 200, part of the plurality of constituent elementsindicated in FIG. 10 , etc. may be mounted, and a video can beefficiently processed with a small coding amount by means of part of theabove-described processes being executed.

[Supplement]

Encoder 100 and decoder 200 according to each of the embodiments may beused as an image encoder and an image decoder, or may be used as a videoencoder and a video decoder. Alternatively, each of encoder 100 anddecoder 200 can be used as an inter prediction apparatus. In otherwords, encoder 100 and decoder 200 may correspond only to interpredictor 126 and inter predictor 218, respectively.

In addition, although a prediction block is encoded or decoded or acurrent block to be encoded or a current block to be decoded in each ofthe embodiments, current blocks to be encoded or current blocks to bedecoded are not limited to a prediction block, and may be a sub-block,or another block.

In addition, in each of the embodiments, each of the constituentelements may be configured with exclusive hardware, or may beimplemented by executing a software program suitable for eachconstituent element. Each constituent element may be implemented bymeans of a program executor that is a CPU, a processor, or the likereading and executing a software program stored in a recording mediumthat is a hard disc, a semiconductor memory, or the like.

More specifically, each of encoder 100 and decoder 200 may includeprocessing circuitry and storage electrically connected to theprocessing circuitry and accessible from the processing circuitry.

The processing circuitry includes at least one of the exclusive hardwareand the program executor. In addition, when the processing circuitryincludes the program executor, the storage stores a software programthat is executed by the program executor.

Here, the software which implements encoder 100, decoder 200, etc.,according to each of the embodiments is a program as indicated below.

More specifically, this program causes a computer to execute processingaccording to any of the flowcharts in FIGS. 5B, 5D, 11, 13, 14, 16, 19,20, 22, and 28 .

The respective constituent elements may be circuits as described above.These circuits may be configured with a single circuit as a whole, ormay be respectively configured with separate circuits. Alternatively,each constituent element may be implemented as a general processor, ormay be implemented as an exclusive processor.

In addition, the processing that is executed by a particular constituentelement may be executed by another constituent element. In addition, theprocessing execution order may be modified, or a plurality of processesmay be executed in parallel. In addition, an encoder and decoder mayinclude encoder 100 and decoder 200.

In addition, the ordinal numbers such as “first” and “second” used forexplanation may be arbitrarily changed. A new ordinal number may beattached to a constituent element, or an ordinal number attached to aconstituent element may be removed.

Although some aspects of encoder 100 and decoder 200 have been explainedbased on the above embodiments, aspects of encoder 100 and decoder 200are not limited to these embodiments. The scope of the aspects ofencoder 100 and decoder 200 may encompass embodiments obtainable byadding, to any of these embodiments, various kinds of modifications thata person skilled in the art would arrive at without deviating from thescope of the present disclosure and embodiments configurable byarbitrarily combining constituent elements in different embodiments.

Embodiment 8

In each of the embodiments, each of the functional blocks can normallybe implemented as an MPU, memory, or the like. In addition, theprocessing performed by each functional block is normally implemented bya program executor such as a processor reading and executing software (aprogram) recorded on a recording medium such as a ROM. The software maybe distributed by download, or the like, or may be recorded on arecording medium such as a semiconductor memory and then be distributed.It is to be noted that each functional block can naturally beimplemented as hardware (an exclusive circuit).

In addition, the processing described in each embodiment may beimplemented by performing centralized processing using a singleapparatus (system), or by performing distributed processing using aplurality of apparatuses. In addition, one or more processors mayexecute the program. In other words, any one of centralized processingand distributed processing may be performed.

Aspects of the present disclosure are not limited to the above examples,various modifications are possible, and these modifications, etc. may beencompassed in aspects of the present disclosure.

Furthermore, here, application examples of a video encoding method(image encoding method) or a video decoding method (image decodingmethod) indicated in each of the embodiments and a system using theapplication examples are described. The system is characterized byincluding an image encoder which performs an image encoding method, animage decoder which performs an image decoding method, and an imageencoder and decoder which performs both an image encoding method and animage decoding method. The other constituent elements in the system canbe appropriately modified according to cases.

Usage Examples

FIG. 44 illustrates an overall configuration of content providing systemex100 for implementing a content distribution service. The area in whichthe communication service is provided is divided into cells of desiredsizes, and base stations ex106, ex107, ex108, ex109, and ex110, whichare fixed wireless stations, are located in respective cells.

In content providing system ex100, devices including computer ex111,gaming device ex112, camera ex113, home appliance ex114, and smartphoneex115 are connected to internet ex101 via internet service providerex102 or communications network ex104 and base stations ex106 throughex110. Content providing system ex100 may combine and connect anycombination of the above elements. The devices may be directly orindirectly connected together via a telephone network or near fieldcommunication rather than via base stations ex106 through ex110, whichare fixed wireless stations. Moreover, streaming server ex103 isconnected to devices including computer ex111, gaming device ex112,camera ex113, home appliance ex114, and smartphone ex115 via, forexample, internet ex101. Streaming server ex103 is also connected to,for example, a terminal in a hotspot in airplane ex117 via satelliteex116.

Note that instead of base stations ex106 through ex110, wireless accesspoints or hotspots may be used. Streaming server ex103 may be connectedto communications network ex104 directly instead of via internet ex101or internet service provider ex102, and may be connected to airplaneex117 directly instead of via satellite ex116.

Camera ex113 is a device capable of capturing still images and video,such as a digital camera. Smartphone ex115 is a smartphone device,cellular phone, or personal handyphone system (PHS) phone that canoperate under the mobile communications system standards of the typical2G, 3G, 3.9G, and 4G systems, as well as the next-generation 5G system.

Home appliance ex118 is, for example, a refrigerator or a deviceincluded in a home fuel cell cogeneration system.

In content providing system ex100, a terminal including an image and/orvideo capturing function is capable of, for example, live streaming byconnecting to streaming server ex103 via, for example, base stationex106. When live streaming, a terminal (e.g., computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, orairplane ex117) performs the encoding processing described in the aboveembodiments on still-image or video content captured by a user via theterminal, multiplexes video data obtained via the encoding and audiodata obtained by encoding audio corresponding to the video, andtransmits the obtained data to streaming server ex103. In other words,the terminal functions as the image encoder according to one aspect ofthe present disclosure.

Streaming server ex103 streams transmitted content data to clients thatrequest the stream. Client examples include computer ex111, gamingdevice ex112, camera ex113, home appliance ex114, smartphone ex115, andterminals inside airplane ex117, which are capable of decoding theabove-described encoded data. Devices that receive the streamed datadecode and reproduce the received data. In other words, the devices eachfunction as the image decoder according to one aspect of the presentdisclosure.

[Decentralized Processing]

Streaming server ex103 may be realized as a plurality of servers orcomputers between which tasks such as the processing, recording, andstreaming of data are divided. For example, streaming server ex103 maybe realized as a content delivery network (CDN) that streams content viaa network connecting multiple edge servers located throughout the world.In a CDN, an edge server physically near the client is dynamicallyassigned to the client. Content is cached and streamed to the edgeserver to reduce load times. In the event of, for example, some kind ofan error or a change in connectivity due to, for example, a spike intraffic, it is possible to stream data stably at high speeds since it ispossible to avoid affected parts of the network by, for example,dividing the processing between a plurality of edge servers or switchingthe streaming duties to a different edge server, and continuingstreaming.

Decentralization is not limited to just the division of processing forstreaming; the encoding of the captured data may be divided between andperformed by the terminals, on the server side, or both. In one example,in typical encoding, the processing is performed in two loops. The firstloop is for detecting how complicated the image is on a frame-by-frameor scene-by-scene basis, or detecting the encoding load. The second loopis for processing that maintains image quality and improves encodingefficiency. For example, it is possible to reduce the processing load ofthe terminals and improve the quality and encoding efficiency of thecontent by having the terminals perform the first loop of the encodingand having the server side that received the content perform the secondloop of the encoding. In such a case, upon receipt of a decodingrequest, it is possible for the encoded data resulting from the firstloop performed by one terminal to be received and reproduced on anotherterminal in approximately real time. This makes it possible to realizesmooth, real-time streaming.

In another example, camera ex113 or the like extracts a feature amountfrom an image, compresses data related to the feature amount asmetadata, and transmits the compressed metadata to a server. Forexample, the server determines the significance of an object based onthe feature amount and changes the quantization accuracy accordingly toperform compression suitable for the meaning of the image. Featureamount data is particularly effective in improving the precision andefficiency of motion vector prediction during the second compressionpass performed by the server. Moreover, encoding that has a relativelylow processing load, such as variable length coding (VLC), may behandled by the terminal, and encoding that has a relatively highprocessing load, such as context-adaptive binary arithmetic coding(CABAC), may be handled by the server.

In yet another example, there are instances in which a plurality ofvideos of approximately the same scene are captured by a plurality ofterminals in, for example, a stadium, shopping mall, or factory. In sucha case, for example, the encoding may be decentralized by dividingprocessing tasks between the plurality of terminals that captured thevideos and, if necessary, other terminals that did not capture thevideos and the server, on a per-unit basis. The units may be, forexample, groups of pictures (GOP), pictures, or tiles resulting fromdividing a picture. This makes it possible to reduce load times andachieve streaming that is closer to real-time.

Moreover, since the videos are of approximately the same scene,management and/or instruction may be carried out by the server so thatthe videos captured by the terminals can be cross-referenced. Moreover,the server may receive encoded data from the terminals, change referencerelationship between items of data or correct or replace picturesthemselves, and then perform the encoding. This makes it possible togenerate a stream with increased quality and efficiency for theindividual items of data.

Moreover, the server may stream video data after performing transcodingto convert the encoding format of the video data. For example, theserver may convert the encoding format from MPEG to VP, and may convert11.264 to 11.265.

In this way, encoding can be performed by a terminal or one or moreservers. Accordingly, although the device that performs the encoding isreferred to as a “server” or “terminal” in the following description,some or all of the processes performed by the server may be performed bythe terminal, and likewise some or all of the processes performed by theterminal may be performed by the server. This also applies to decodingprocesses.

[3D, Multi-Angle]

In recent years, usage of images or videos combined from images orvideos of different scenes concurrently captured or the same scenecaptured from different angles by a plurality of terminals such ascamera ex113 and/or smartphone ex115 has increased. Videos captured bythe terminals are combined based on, for example, theseparately-obtained relative positional relationship between theterminals, or regions in a video having matching feature points.

In addition to the encoding of two-dimensional moving pictures, theserver may encode a still image based on scene analysis of a movingpicture either automatically or at a point in time specified by theuser, and transmit the encoded still image to a reception terminal.Furthermore, when the server can obtain the relative positionalrelationship between the video capturing terminals, in addition totwo-dimensional moving pictures, the server can generatethree-dimensional geometry of a scene based on video of the same scenecaptured from different angles. Note that the server may separatelyencode three-dimensional data generated from, for example, a pointcloud, and may, based on a result of recognizing or tracking a person orobject using three-dimensional data, select or reconstruct and generatea video to be transmitted to a reception terminal from videos capturedby a plurality of terminals.

This allows the user to enjoy a scene by freely selecting videoscorresponding to the video capturing terminals, and allows the user toenjoy the content obtained by extracting, from three-dimensional datareconstructed from a plurality of images or videos, a video from aselected viewpoint. Furthermore, similar to with video, sound may berecorded from relatively different angles, and the server may multiplex,with the video, audio from a specific angle or space in accordance withthe video, and transmit the result.

In recent years, content that is a composite of the real world and avirtual world, such as virtual reality (VR) and augmented reality (AR)content, has also become popular. In the case of VR images, the servermay create images from the viewpoints of both the left and right eyesand perform encoding that tolerates reference between the two viewpointimages, such as multi-view coding (MVC), and, alternatively, may encodethe images as separate streams without referencing. When the images aredecoded as separate streams, the streams may be synchronized whenreproduced so as to recreate a virtual three-dimensional space inaccordance with the viewpoint of the user.

In the case of AR images, the server superimposes virtual objectinformation existing in a virtual space onto camera informationrepresenting a real-world space, based on a three-dimensional positionor movement from the perspective of the user. The decoder may obtain orstore virtual object information and three-dimensional data, generatetwo-dimensional images based on movement from the perspective of theuser, and then generate superimposed data by seamlessly connecting theimages. Alternatively, the decoder may transmit, to the server, motionfrom the perspective of the user in addition to a request for virtualobject information, and the server may generate superimposed data basedon three-dimensional data stored in the server in accordance with thereceived motion, and encode and stream the generated superimposed datato the decoder. Note that superimposed data includes, in addition to RGBvalues, an α value indicating transparency, and the server sets the avalue for sections other than the object generated fromthree-dimensional data to, for example, 0, and may perform the encodingwhile those sections are transparent. Alternatively, the server may setthe background to a predetermined RGB value, such as a chroma key, andgenerate data in which areas other than the object are set as thebackground.

Decoding of similarly streamed data may be performed by the client(i.e., the terminals), on the server side, or divided therebetween. Inone example, one terminal may transmit a reception request to a server,the requested content may be received and decoded by another terminal,and a decoded signal may be transmitted to a device having a display. Itis possible to reproduce high image quality data by decentralizingprocessing and appropriately selecting content regardless of theprocessing ability of the communications terminal itself. In yet anotherexample, while a TV, for example, is receiving image data that is largein size, a region of a picture, such as a tile obtained by dividing thepicture, may be decoded and displayed on a personal terminal orterminals of a viewer or viewers of the TV. This makes it possible forthe viewers to share a big-picture view as well as for each viewer tocheck his or her assigned area or inspect a region in further detail upclose.

In the future, both indoors and outdoors, in situations in which aplurality of wireless connections are possible over near, mid, and fardistances, it is expected to be able to seamlessly receive content evenwhen switching to data appropriate for the current connection, using astreaming system standard such as MPEG-DASH. With this, the user canswitch between data in real time while freely selecting a decoder ordisplay apparatus including not only his or her own terminal, but also,for example, displays disposed indoors or outdoors. Moreover, based on,for example, information on the position of the user, decoding can beperformed while switching which terminal handles decoding and whichterminal handles the displaying of content. This makes it possible to,while in route to a destination, display, on the wall of a nearbybuilding in which a device capable of displaying content is embedded oron part of the ground, map information while on the move. Moreover, itis also possible to switch the bit rate of the received data based onthe accessibility to the encoded data on a network, such as when encodeddata is cached on a server quickly accessible from the receptionterminal or when encoded data is copied to an edge server in a contentdelivery service.

[Scalable Encoding]

The switching of content will be described with reference to a scalablestream, illustrated in FIG. 45 , that is compression coded viaimplementation of the moving picture encoding method described in theabove embodiments. The server may have a configuration in which contentis switched while making use of the temporal and/or spatial scalabilityof a stream, which is achieved by division into and encoding of layers,as illustrated in FIG. 45 . Note that there may be a plurality ofindividual streams that are of the same content but different quality.In other words, by determining which layer to decode up to based oninternal factors, such as the processing ability on the decoder side,and external factors, such as communication bandwidth, the decoder sidecan freely switch between low resolution content and high resolutioncontent while decoding. For example, in a case in which the user wantsto continue watching, at home on a device such as a TV connected to theinternet, a video that he or she had been previously watching onsmartphone ex115 while on the move, the device can simply decode thesame stream up to a different layer, which reduces server side load.

Furthermore, in addition to the configuration described above in whichscalability is achieved as a result of the pictures being encoded perlayer and the enhancement layer is above the base layer, the enhancementlayer may include metadata based on, for example, statisticalinformation on the image, and the decoder side may generate high imagequality content by performing super-resolution imaging on a picture inthe base layer based on the metadata. Super-resolution imaging may beimproving the SN ratio while maintaining resolution and/or increasingresolution. Metadata includes information for identifying a linear or anon-linear filter coefficient used in super-resolution processing, orinformation identifying a parameter value in filter processing, machinelearning, or least squares method used in super-resolution processing.

Alternatively, a configuration in which a picture is divided into, forexample, tiles in accordance with the meaning of, for example, an objectin the image, and on the decoder side, only a partial region is decodedby selecting a tile to decode, is also acceptable. Moreover, by storingan attribute about the object (person, car, ball, etc.) and a positionof the object in the video (coordinates in identical images) asmetadata, the decoder side can identify the position of a desired objectbased on the metadata and determine which tile or tiles include thatobject. For example, as illustrated in FIG. 46 , metadata is storedusing a data storage structure different from pixel data such as an SEImessage in HEVC. This metadata indicates, for example, the position,size, or color of the main object.

Moreover, metadata may be stored in units of a plurality of pictures,such as stream, sequence, or random access units. With this, the decoderside can obtain, for example, the time at which a specific personappears in the video, and by fitting that with picture unit information,can identify a picture in which the object is present and the positionof the object in the picture.

[Web Page Optimization]

FIG. 47 illustrates an example of a display screen of a web page on, forexample, computer ex111. FIG. 48 illustrates an example of a displayscreen of a web page on, for example, smartphone ex115. As illustratedin FIG. 47 and FIG. 48 , a web page may include a plurality of imagelinks which are links to image content, and the appearance of the webpage differs depending on the device used to view the web page. When aplurality of image links are viewable on the screen, until the userexplicitly selects an image link, or until the image link is in theapproximate center of the screen or the entire image link fits in thescreen, the display apparatus (decoder) displays, as the image links,still images included in the content or I pictures, displays video suchas an animated gif using a plurality of still images or I pictures, forexample, or receives only the base layer and decodes and displays thevideo.

When an image link is selected by the user, the display apparatusdecodes giving the highest priority to the base layer. Note that ifthere is information in the HTML code of the web page indicating thatthe content is scalable, the display apparatus may decode up to theenhancement layer. Moreover, in order to guarantee real timereproduction, before a selection is made or when the bandwidth isseverely limited, the display apparatus can reduce delay between thepoint in time at which the leading picture is decoded and the point intime at which the decoded picture is displayed (that is, the delaybetween the start of the decoding of the content to the displaying ofthe content) by decoding and displaying only forward reference pictures(I picture, P picture, forward reference B picture). Moreover, thedisplay apparatus may purposely ignore the reference relationshipbetween pictures and coarsely decode all B and P pictures as forwardreference pictures, and then perform normal decoding as the number ofpictures received over time increases.

[Autonomous Driving]

When transmitting and receiving still image or video data such two- orthree-dimensional map information for autonomous driving or assisteddriving of an automobile, the reception terminal may receive, inaddition to image data belonging to one or more layers, information on,for example, the weather or road construction as metadata, and associatethe metadata with the image data upon decoding. Note that metadata maybe assigned per layer and, alternatively, may simply be multiplexed withthe image data.

In such a case, since the automobile, drone, airplane, etc., includingthe reception terminal is mobile, the reception terminal can seamlesslyreceive and decode while switching between base stations among basestations ex106 through ex110 by transmitting information indicating theposition of the reception terminal upon reception request. Moreover, inaccordance with the selection made by the user, the situation of theuser, or the bandwidth of the connection, the reception terminal candynamically select to what extent the metadata is received or to whatextent the map information, for example, is up dated.

With this, in content providing system ex100, the client can receive,decode, and reproduce, in real time, encoded information transmitted bythe user.

[Streaming of Individual Content]

In content providing system ex100, in addition to high image quality,long content distributed by a video distribution entity, unicast ormulticast streaming of low image quality, short content from anindividual is also possible. Moreover, such content from individuals islikely to further increase in popularity. The server may first performediting processing on the content before the encoding processing inorder to refine the individual content. This may be achieved with, forexample, the following configuration.

In real-time while capturing video or image content or after the contenthas been captured and accumulated, the server performs recognitionprocessing based on the raw or encoded data, such as capture errorprocessing, scene search processing, meaning analysis, and/or objectdetection processing. Then, based on the result of the recognitionprocessing, the server—either when prompted or automatically—edits thecontent, examples of which include: correction such as focus and/ormotion blur correction; removing low-priority scenes such as scenes thatare low in brightness compared to other pictures or out of focus; objectedge adjustment; and color tone adjustment. The server encodes theedited data based on the result of the editing. It is known thatexcessively long videos tend to receive fewer views. Accordingly, inorder to keep the content within a specific length that scales with thelength of the original video, the server may, in addition to thelow-priority scenes described above, automatically clip out scenes withlow movement based on an image processing result. Alternatively, theserver may generate and encode a video digest based on a result of ananalysis of the meaning of a scene.

Note that there are instances in which individual content may includecontent that infringes a copyright, moral right, portrait rights, etc.Such an instance may lead to an unfavorable situation for the creator,such as when content is shared beyond the scope intended by the creator.Accordingly, before encoding, the server may, for example, edit imagesso as to blur faces of people in the periphery of the screen or blur theinside of a house, for example. Moreover, the server may be configuredto recognize the faces of people other than a registered person inimages to be encoded, and when such faces appear in an image, forexample, apply a mosaic filter to the face of the person. Alternatively,as pre- or post-processing for encoding, the user may specify, forcopyright reasons, a region of an image including a person or a regionof the background be processed, and the server may process the specifiedregion by, for example, replacing the region with a different image orblurring the region. If the region includes a person, the person may betracked in the moving picture the head region may be replaced withanother image as the person moves.

Moreover, since there is a demand for real-time viewing of contentproduced by individuals, which tends to be small in data size, thedecoder first receives the base layer as the highest priority andperforms decoding and reproduction, although this may differ dependingon bandwidth. When the content is reproduced two or more times, such aswhen the decoder receives the enhancement layer during decoding andreproduction of the base layer and loops the reproduction, the decodermay reproduce a high image quality video including the enhancementlayer. If the stream is encoded using such scalable encoding, the videomay be low quality when in an unselected state or at the start of thevideo, but it can offer an experience in which the image quality of thestream progressively increases in an intelligent manner. This is notlimited to just scalable encoding; the same experience can be offered byconfiguring a single stream from a low quality stream reproduced for thefirst time and a second stream encoded using the first stream as areference.

Other Usage Examples

The encoding and decoding may be performed by LSI ex500, which istypically included in each terminal. LSI ex500 may be configured of asingle chip or a plurality of chips. Software for encoding and decodingmoving pictures may be integrated into some type of a recording medium(such as a CD-ROM, a flexible disk, or a hard disk) that is readable by,for example, computer ex111, and the encoding and decoding may beperformed using the software. Furthermore, when smartphone ex115 isequipped with a camera, the video data obtained by the camera may betransmitted. In this case, the video data is coded by LSI ex500 includedin smartphone ex115.

Note that LSI ex500 may be configured to download and activate anapplication. In such a case, the terminal first determines whether it iscompatible with the scheme used to encode the content or whether it iscapable of executing a specific service. When the terminal is notcompatible with the encoding scheme of the content or when the terminalis not capable of executing a specific service, the terminal firstdownloads a codec or application software then obtains and reproducesthe content.

Aside from the example of content providing system ex100 that usesinternet ex101, at least the moving picture encoder (image encoder) orthe moving picture decoder (image decoder) described in the aboveembodiments may be implemented in a digital broadcasting system. Thesame encoding processing and decoding processing may be applied totransmit and receive broadcast radio waves superimposed with multiplexedaudio and video data using, for example, a satellite, even though thisis geared toward multicast whereas unicast is easier with contentproviding system ex100.

[Hardware Configuration]

FIG. 49 illustrates smartphone ex115. FIG. 50 illustrates aconfiguration example of smartphone ex115. Smartphone ex115 includesantenna ex450 for transmitting and receiving radio waves to and frombase station ex110, camera ex465 capable of capturing video and stillimages, and display ex458 that displays decoded data, such as videocaptured by camera ex465 and video received by antenna ex450. Smartphoneex115 further includes user interface ex466 such as a touch panel, audiooutput unit ex457 such as a speaker for outputting speech or otheraudio, audio input unit ex456 such as a microphone for audio input,memory ex467 capable of storing decoded data such as captured video orstill images, recorded audio, received video or still images, and mail,as well as decoded data, and slot ex464 which is an interface for SIMex468 for authorizing access to a network and various data. Note thatexternal memory may be used instead of memory ex467.

Moreover, main controller ex460 which comprehensively controls displayex458 and user interface ex466, power supply circuit ex461, userinterface input controller ex462, video signal processor ex455, camerainterface ex463, display controller ex459, modulator/demodulator ex452,multiplexer/demultiplexer ex453, audio signal processor ex454, slotex464, and memory ex467 are connected via bus ex470.

When the user turns the power button of power supply circuit ex461 on,smartphone ex115 is powered on into an operable state by each componentbeing supplied with power from a battery pack.

Smartphone ex115 performs processing for, for example, calling and datatransmission, based on control performed by main controller ex460, whichincludes a CPU, ROM, and RAM. When making calls, an audio signalrecorded by audio input unit ex456 is converted into a digital audiosignal by audio signal processor ex454, and this is applied with spreadspectrum processing by modulator/demodulator ex452 and digital-analogconversion and frequency conversion processing by transmitter/receiverex451, and then transmitted via antenna ex450. The received data isamplified, frequency converted, and analog-digital converted, inversespread spectrum processed by modulator/demodulator ex452, converted intoan analog audio signal by audio signal processor ex454, and then outputfrom audio output unit ex457. In data transmission mode, text,still-image, or video data is transmitted by main controller ex460 viauser interface input controller ex462 as a result of operation of, forexample, user interface ex466 of the main body, and similar transmissionand reception processing is performed. In data transmission mode, whensending a video, still image, or video and audio, video signal processorex455 compression encodes, via the moving picture encoding methoddescribed in the above embodiments, a video signal stored in memoryex467 or a video signal input from camera ex465, and transmits theencoded video data to multiplexer/demultiplexer ex453. Moreover, audiosignal processor ex454 encodes an audio signal recorded by audio inputunit ex456 while camera ex465 is capturing, for example, a video orstill image, and transmits the encoded audio data tomultiplexer/demultiplexer ex453. Multiplexer/demultiplexer ex453multiplexes the encoded video data and encoded audio data using apredetermined scheme, modulates and converts the data usingmodulator/demodulator (modulator/demodulator circuit) ex452 andtransmitter/receiver ex451, and transmits the result via antenna ex450.

When video appended in an email or a chat, or a video linked from a webpage, for example, is received, in order to decode the multiplexed datareceived via antenna ex450, multiplexer/demultiplexer ex453demultiplexes the multiplexed data to divide the multiplexed data into abitstream of video data and a bitstream of audio data, supplies theencoded video data to video signal processor ex455 via synchronous busex470, and supplies the encoded audio data to audio signal processorex454 via synchronous bus ex470. Video signal processor ex455 decodesthe video signal using a moving picture decoding method corresponding tothe moving picture encoding method described in the above embodiments,and video or a still image included in the linked moving picture file isdisplayed on display ex458 via display controller ex459. Moreover, audiosignal processor ex454 decodes the audio signal and outputs audio fromaudio output unit ex457. Note that since real-time streaming is becomingmore and more popular, there are instances in which reproduction of theaudio may be socially inappropriate depending on the user's environment.Accordingly, as an initial value, a configuration in which only videodata is reproduced, i.e., the audio signal is not reproduced, ispreferable. Audio may be synchronized and reproduced only when an input,such as when the user clicks video data, is received.

Although smartphone ex115 was used in the above example, threeimplementations are conceivable: a transceiver terminal including bothan encoder and a decoder; a transmitter terminal including only anencoder; and a receiver terminal including only a decoder. Further, inthe description of the digital broadcasting system, an example is givenin which multiplexed data obtained as a result of video data beingmultiplexed with, for example, audio data, is received or transmitted,but the multiplexed data may be video data multiplexed with data otherthan audio data, such as text data related to the video. Moreover, thevideo data itself rather than multiplexed data maybe received ortransmitted.

Although main controller ex460 including a CPU is described ascontrolling the encoding or decoding processes, terminals often includeGPUs. Accordingly, a configuration is acceptable in which a large areais processed at once by making use of the performance ability of the GPUvia memory shared by the CPU and GPU or memory including an address thatis managed so as to allow common usage by the CPU and GPU. This makes itpossible to shorten encoding time, maintain the real-time nature of thestream, and reduce delay. In particular, processing relating to motionestimation, deblocking filtering, sample adaptive offset (SAO), andtransformation/quantization can be effectively carried out by the GPUinstead of the CPU in units of, for example pictures, all at once.

What is claimed is:
 1. A decoder comprising: a memory; and processingcircuitry, which is coupled to the memory and which, in operation,changes values of pixels in a first block and a second block to filter aboundary between the first block and the second block, using clippingsuch that change amounts of the respective values are within respectiveclip widths, the pixels in the first block and the second block beingarranged along a straight line across the boundary; wherein the pixelsin the first block include a first pixel located at a first position,and the pixels in the second block include a second pixel located at asecond position corresponding to the first position with respect to theboundary; wherein the clip widths include a first clip width and asecond clip width corresponding to the first pixel and the second pixel,respectively; wherein the first clip width is different from the secondclip width; wherein the pixels in the first block include a firstadditional pixel located at a first additional position and the pixelsin the second block include a second additional pixel located at asecond additional position which corresponds to the first additionalposition with respect to the boundary; wherein the clip widths include afirst additional clip width and a second additional clip widthcorresponding to the first additional pixel and the second additionalpixel, respectively; and wherein the first additional clip width is sameas the second additional clip width.